Journal articles on the topic 'Engine look-up tables'
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1
Stotsky, A. A. "Data-driven algorithms for engine friction estimation." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 221, no. 7 (July 1, 2007): 901–9. http://dx.doi.org/10.1243/09544070jauto230.
Abstract:
Errors in the estimation of friction torque in modern spark ignition automotive engines necessitate the development of real-time algorithms for adaptation of the friction torque. Friction torque in the engine control unit is presented as a look-up table with two input variables (the engine speed and indicated engine torque). The algorithms proposed in this paper estimate the engine friction torque via the crankshaft speed fluctuations at the fuel cut-off state and at idle. A computationally efficient filtering algorithm for reconstruction of the first harmonic of a periodic signal is used to recover an amplitude which corresponds to engine events from the noise-contaminated engine speed measurements at the fuel cut-off state. The values of the friction torque at the nodes of the look-up table are updated, when new measured data of the friction torque are available. New data-driven algorithms which are based on a stepwise regression method are developed for adaptation of look-up tables. The algorithms are verified by using a spark ignition six-cylinder prototype engine.
2
Bastian, Andreas. "Modeling Fuel Injection Control Maps Using Fuzzy Logic and Neural Networks." Journal of Robotics and Mechatronics 6, no. 4 (August 20, 1994): 340–44. http://dx.doi.org/10.20965/jrm.1994.p0340.
Abstract:
Determining the correct ignition point of the air-fuel mixture is critical in order to achieve maximum output torque and to reduce exhaust emissions. In some fuel injection control systems the amount of air cannot be detected, thus, look-up tables are utilized, which contain the amount of air for given engine speed and inlet manifold pressure. In this paper, we model the look-up table using fuzzy logic. A neural network approach is used to identify the inputs of the fuzzy model.
3
Hausberg, F., M. Plöchl, M. Rupp, P. Pfeffer, and S. Hecker. "Combination of map-based and adaptive feedforward control algorithms for active engine mounts." Journal of Vibration and Control 23, no. 19 (January 20, 2016): 3092–107. http://dx.doi.org/10.1177/1077546315626323.
Abstract:
Active engine mounts significantly contribute to ensure the comfort in vehicles with emission-reducing engine technologies, e.g., cylinder-on-demand (COD), downsizing or turbochargers. To control active engine mounts, either adaptive or non-adaptive feedforward control is commonly employed. Since both approaches have previously been treated separately, this study proposes methods to connect them in terms of multiple-input-multiple-output Newton/FxLMS adaptive filters with self-trained, grid-based look-up tables. The look-up tables are incorporated as parameter-maps or parallel-maps, respectively. By combining the two feedforward control strategies, their inherent advantages, i.e., the adaptivity of adaptive filtering and the direct impact as well as the tracking behavior of map-based feedforward control, are utilized. The proposed control structures are illustrated by simulation and experimentally demonstrated in a vehicle with a V8-COD engine. While both methods significantly reduce the convergence time of the adaptive filter, the parallel implementation additionally improves the tracking behavior during fast engine run-ups.
4
Vogt, Michael, Norbert Mu¨ller, and Rolf Isermann. "On-Line Adaptation of Grid-Based Look-up Tables Using a Fast Linear Regression Technique." Journal of Dynamic Systems, Measurement, and Control 126, no. 4 (December 1, 2004): 732–39. http://dx.doi.org/10.1115/1.1849241.
Abstract:
Advanced control systems require accurate process models, while processes are often both nonlinear and time variant. After introducing the identification of nonlinear processes with grid-based look-up tables, a new learning algorithm for on-line adaptation of look-up tables is proposed. Using a linear regression approach, this new adaptation algorithm considerably reduces the convergence time in relation to conventional gradient-based adaptation algorithms. An application example and experimental results are shown for the learning feedforward control of the ignition angle of a spark ignition engine.
5
Puleston, P. F., G. Monsees, and S. K. Spurgeon. "Air-fuel ratio and speed control for low emission vehicles based on sliding mode techniques." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 216, no. 2 (March 1, 2002): 117–24. http://dx.doi.org/10.1243/0959651021541480.
Abstract:
This paper deals with the combined air-fuel ratio (AFR) and speed control of automotive engines. The robust controller is developed using dynamic sliding mode (SM) control design methods. The proposed controller set-up is tested under realistic operating conditions by means of computer simulation using a comprehensive non-linear model of a four-stroke engine, specifically provided by the automotive industry for these purposes. This accurate industrial model comprises extensive dynamics description and numerous look-up tables representing parameter characteristics obtained from experimental data. The SM controller set-up proves to be robust to model uncertainties and unknown disturbances, regulating effectively the engine speed for a wide range of set-points while maintaining the AFR at the stoichiometric value.
6
Dilibe, Ifeanyi. "Computational model of the fuel consumption and exhaust temperature of a heavy duty diesel engine using MATLAB/SIMULINK." Poljoprivredna tehnika 45, no. 4 (2020): 51–70. http://dx.doi.org/10.5937/poljteh2004051d.
Abstract:
A model of a diesel engine and its electronic control system was developed to investigate the engine behaviour in a vehicle simulation environment. The modelled quantities were brake torque, fuel consumption and exhaust gas temperature and were based on engine speed and pedal position. In order to describe these outputs the inlet air flow and boost pressure were also modelled and used as inner variables. The model was intended to be implemented on board a vehicle in a control unit which had limited computational performance. To keep the model as computationally efficient as possible the model basically consists of look-up tables and polynomials. First order systems were used to describe the dynamics of air flow and exhaust temperature. The outputs enable gear shift optimization over three variables, torque for vehicle acceleration, fuel consumption for efficiency and exhaust temperature to maintain high efficiency in the exhaust after treatment system. The engine model captures the low frequent dynamics of the modelled quantities in the closed loop of the engine and its electronic control system. The model only consists of three states, one for the pressure build up in the intake manifold and two states for modelling the exhaust temperature. The model was compared to measured data from an engine test cell (as got in INNOSON NIG. LTD.) and the mean absolute relative error were lower than 6.8%, 7.8% and 5.8% for brake torque, fuel consumption and exhaust gas temperature respectively. These results were considered good given the simplicity of the model.
7
Zhang, Haibo, and Fengyong Sun. "Direct Surge Margin Control for Aeroengines Based on Improved SVR Machine and LQR Method." Mathematical Problems in Engineering 2013 (2013): 1–17. http://dx.doi.org/10.1155/2013/870215.
Abstract:
A novel scheme of high stability engine control (HISTEC) on the basis of an improved linear quadratic regulator (ILQR), called direct surge margin control, is derived for super-maneuver flights. Direct surge margin control, which is different from conventional control scheme, puts surge margin into the engine closed-loop system and takes surge margin as controlled variable directly. In this way, direct surge margin control can exploit potential performance of engine more effectively with a decrease of engine stability margin which usually happened in super-maneuver flights. For conquering the difficulty that aeroengine surge margin is undetectable, an approach based on improved support vector regression (SVR) machine is proposed to construct a surge margin prediction model. The surge margin modeling contains two parts: a baseline model under no inlet distortion states and the calculation for surge margin loss under supermaneuvering flight conditions. The previous one is developed using neural network method, the inputs of which are selected by a weighted feature selection algorithm. Considering the hysteresis between pilot input and angle of attack output, an online scrolling window least square support vector regression (LSSVR) method is employed to firstly estimate inlet distortion index and further compute surge margin loss via some empirical look-up tables.
8
Zhang, Y., X. Chen, X. Zhang, H. Jiang, and W. Tobler. "Dynamic Modeling and Simulation of a Dual-Clutch Automated Lay-Shaft Transmission." Journal of Mechanical Design 127, no. 2 (March 1, 2005): 302–7. http://dx.doi.org/10.1115/1.1829069.
Abstract:
This paper presents a systematic model for the simulation and analysis of a power-shift transmission that features a dual-clutch design. The paper models the kinematics, dynamics, and control of the transmission for the analysis of powertrain overall performance and shift transient characteristics. The model is implemented in an object-oriented software tool. Analytical formulations and look-up tables are both used for modeling of powertrain components. The vehicle system model is established by integrating the various components and subsystem models according to the transmission power flow and control logic. The input to the simulation model is the vehicle speed-time profile and the output provides the speed follow-up, engine, and clutch operation status for the drive range and shift processes involved. As a numerical example, the model is used for a vehicle equipped with the power-shift transmission to simulate the speed follow-up over a specified drive range and the dynamic transients during shifts.© 2004 American Institute of Physics.
9
Marinoni, Andrea Massimo, Angelo Onorati, Giacomo Manca Di Villahermosa, and Simon Langridge. "Real Driving Cycle Simulation of a Hybrid Bus by Means of a Co-Simulation Tool for the Prediction of Performance and Emissions." Energies 16, no. 12 (June 15, 2023): 4736. http://dx.doi.org/10.3390/en16124736.
Abstract:
This work is focused on the simulation of a complete hybrid bus vehicle model performing a real-world driving cycle. The simulation framework consists of a coupled co-simulation environment, where all the vehicle sub-system models are linked to achieve a real time exchange of input and output signals. In the vehicle model also the electric devices of the powertrain and accumulation system are included. This co-simulation platform is applied to investigate the hybridization of a 12-m city bus, performing a typical urban driving mission. A comparison between the conventional powertrain is performed against the hybridized version, to highlight the advantages and challenges. In particular, the novelty of this modeling approach is that the IC engine simulation does not rely on pre-processed look-up tables, but exploits a high-fidelity one-dimensional thermo-fluid dynamic model. However, it was necessary to develop a fast simulation methodology to exploit this predictive tool, achieving a low computational cost. The 1D engine model is first validated against the experimental engine map data available, showing a good model predictivity. Then the 1D engine model and the other models of the powertrain are coupled to the vehicle model, in order to follow the prescribed velocity profile of the driving cycle. The complete model is applied under different conditions, to evaluate the impact on performance and emissions and assess the simulation predictivity.
10
Dowell, Peter G., Sam Akehurst, and Richard D. Burke. "Characterisation and optimisation of a real-time diesel engine model." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 231, no. 14 (February 1, 2017): 1913–34. http://dx.doi.org/10.1177/0954407017691618.
Abstract:
Accurate real-time engine models are an essential step to allow the development of control algorithms in parallel to the development of engine hardware using hardware-in-the-loop applications. A physics-based model of the engine high-pressure air path and combustion chamber is presented. The model was parameterised using data from a small set of carefully selected operating conditions for a 2.0 l diesel engine. The model was subsequently validated over the complete engine operating map with exhaust gas recirculation and without exhaust gas recirculation. A high level of fit was achieved with R2 values above 0.94 for the mean effective pressure and above 0.99 for the air flow rate. The model run time was then reduced for real-time application by using forward differencing and single-precision floating-point numbers and by calculating the in-cylinder prediction for only a single cylinder. A further improvement of 25% in the run time was achieved by improving the submodels, including the strategic use of one-dimensional and two-dimensional look-up tables with optimised resolution. The model exceeds the performance of similar models in the literature, achieving a crank angle resolution of 0.5° at 4000 r/min. This simulation step size still yields good accuracy in comparison with a crank angle resolution of 0.1° and was validated against the experimental results from a New European Driving Cycle. The real-time model allows the development of control strategies before the engine hardware is available, meaning that more time can be spent to ensure that the engine can meet the performance and the emissions requirements over its full operating range.
11
Pla, Benjamin, Joaquin De la Morena, Pau Bares, and Irina Jiménez. "Cycle-to-cycle combustion variability modelling in spark ignited engines for control purposes." International Journal of Engine Research 21, no. 8 (November 1, 2019): 1398–411. http://dx.doi.org/10.1177/1468087419885754.
Abstract:
A control-oriented model of spark ignition combustion is presented. The model makes use of avaliable signals, such as spark advance, air mass, intake pressure, and lambda, to characterize not only the average combustion evolution but also the cycle-to-cycle variability. The conventional turbulent flame propagation model with two states, namely entrained mass and burnt mass, is improved by look-up tables at some parameters, and the cycle-to-cycle variability is estimated by propagation of an exogenous noise with a normal probabilistic distribution at the turbulent and laminar flame speed, which intends to simulate the unknowns at turbulent flow, temperature distribution, or initial kernel distribution. The model is able to estimate which is the expected variability during the combustion evolution and might be used online for characterizing the time response of closed-loop control actions or it can be used offline to improve the control strategies without large experimental test campaigns. Experimental data from a four-stroke commercial engine was used for calibration and validation purposes, demonstrating the capabilities of the model in steady and transient conditions.
12
Frolov, Sergey M., Konstantin A. Avdeev, Vladislav S. Ivanov, Pavel A. Vlasov, Fedor S. Frolov, Ilya V. Semenov, and Marina S. Belotserkovskaya. "Evolution of the Soot-Particle Size Distribution Function in the Cylinder and Exhaust System of Piston Engines: Simulation." Atmosphere 14, no. 1 (December 22, 2022): 13. http://dx.doi.org/10.3390/atmos14010013.
Abstract:
A computational tool for simulating the temporal evolution of the soot-particle size distribution function (SDF) in the internal combustion engine (ICE) and in the attached exhaust pipe is developed and tested against available experimental data on the soot-particle SDF at the outlet of the exhaust system. Firstly, a database of soot particle properties (particle mean diameter, dispersion, total particle number density vs. time for different fuels, fuel-to-air equivalence ratios, temperatures, pressures, and exhaust gas recirculation) is developed based on the thoroughly validated detailed model of soot formation under ICE conditions. The database is organized in the form of look-up tables. Secondly, the soot-particle SDF in the database is approximated using the log-normal SDF, which is directly used in the multidimensional calculations of the ICE operation process. Thirdly, the coagulation model of soot particles is developed, which includes three coagulation mechanisms: Brownian, turbulent–kinetic, and turbulent–diffusion. This model is applied for simulating the evolution of the soot-particle SDF in the exhaust pipe after opening the exhaust valve. Calculations show that the coagulation process of soot particles in the exhaust pipe has a significant effect on the mean size of particles at the outlet of the exhaust system (the mean particle diameter can increase by almost an order of magnitude), and the dominant mechanism of particle coagulation in the exhaust system of a diesel engine is the Brownian mechanism. The objective, approach, and obtained results are the novel features of the study.
13
Beham, M., and D. L. Yu. "On-line control for optimal ignition timing using the pseudolinear radial basis function and the local linear model tree." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 219, no. 2 (February 1, 2005): 227–40. http://dx.doi.org/10.1243/095440705x6712.
Abstract:
A new generation of engines demands new control strategies. The increased number of control variables of variable valve timing engines results in complexity of conventional control structures. This necessitates the integration of new technologies for optimal control of the ignition timing. This paper presents a neural network controller for ignition timing that uses two recently proposed new neural network structures—a pseudolinear radial basis function (PLRBF) network and a local linear model tree (LOLIMOT) network. Tests showed that the relative load signal is not necessary to evaluate the ignition angle, and therefore no air mass meter is necessary. The two neural networks are compared with a conventional look-up table control structure. The network controller improves the conventional look-up table method for calibration by comparison with bilateral look-up tables. The neural controller is implemented and tested in a research car. Experimental results show that the neural networks are very effective in mapping non-linearity. The design of the neural network controller simplifies the structure drastically.
14
Li, Xu, Chuanlei Yang, Yinyan Wang, and Hechun Wang. "A prediction model of compressor with variable-geometry diffuser based on elliptic equation and partial least squares." Royal Society Open Science 5, no. 1 (January 2018): 171468. http://dx.doi.org/10.1098/rsos.171468.
Abstract:
To achieve a much more extensive intake air flow range of the diesel engine, a variable-geometry compressor (VGC) is introduced into a turbocharged diesel engine. However, due to the variable diffuser vane angle (DVA), the prediction for the performance of the VGC becomes more difficult than for a normal compressor. In the present study, a prediction model comprising an elliptical equation and a PLS (partial least-squares) model was proposed to predict the performance of the VGC. The speed lines of the pressure ratio map and the efficiency map were fitted with the elliptical equation, and the coefficients of the elliptical equation were introduced into the PLS model to build the polynomial relationship between the coefficients and the relative speed, the DVA. Further, the maximal order of the polynomial was investigated in detail to reduce the number of sub-coefficients and achieve acceptable fit accuracy simultaneously. The prediction model was validated with sample data and in order to present the superiority of compressor performance prediction, the prediction results of this model were compared with those of the look-up table and back-propagation neural networks (BPNNs). The validation and comparison results show that the prediction accuracy of the new developed model is acceptable, and this model is much more suitable than the look-up table and the BPNN methods under the same condition in VGC performance prediction. Moreover, the new developed prediction model provides a novel and effective prediction solution for the VGC and can be used to improve the accuracy of the thermodynamic model for turbocharged diesel engines in the future.
15
Du, Jia Yi, Hai Ling Li, Deng Pan Zhang, and Yong Jia Lu. "Control Strategy and Realization of Dual Fuel Engine with Intake Premixed Methanol on Turbocharging Diesel Engine." Advanced Materials Research 614-615 (December 2012): 436–40. http://dx.doi.org/10.4028/www.scientific.net/amr.614-615.436.
Abstract:
Based on Methanol and diesel special combustion mode, a control strategy of methanol/diesel dual fuel engine on turbocharged DI diesel engine was introduced according to different operation conditions. A method of judging engine load by measuring intake manifold pressure was put forward. Bicubic interpolation method was adopted to optimize the control MAP for ensuring the coincidence between look-up table data and actual conditions. The feasibility of the control strategy is verified by bench test. And the results of test show that the economic performance of this dual fuel engine got a considerable improvement.
16
Wang, Changhui, and Zhiyuan Liu. "Adaptive sliding mode observer for updating maps with an application to mass air flow sensors in diesel engines." Transactions of the Institute of Measurement and Control 39, no. 12 (June 10, 2016): 1885–97. http://dx.doi.org/10.1177/0142331216650021.
Abstract:
A novel method for mass air flow (MAF) sensor bias compensation and error map (or look-up table) adaptation with model error correction is proposed. A key feature of the approach is its method of handling and storing operating-point-dependent MAF sensor errors due to installation and ageing in diesel engines; such errors lead to adverse impacts on emission performance. The model of the MAF sensor error depending on the engine operating point is represented as a two-dimensional (2D) map, which is described as a piecewise bilinear interpolation model in the form of a vector–vector dot product. The mean-value engine model of a diesel engine with additional model biases is analysed and employed to improve the estimation precision of the 2D map. Based on the combination of the 2D map regression model and diesel engine mean-value engine model with additional model biases, a linear parameter varying adaptive sliding mode observer is designed, which achieves the disturbance suppression for the nonlinear model errors, as well as the simultaneous estimation of the system state, linear model errors and map parameters. The convergence of the proposed algorithm is proven under the conditions of the persistent excitation and given inequalities. The observer is validated against simulation data from the engine software enDYNA provided by TESIS. The results demonstrate that the estimation precision of the MAF sensor error map can be improved using the proposed method.
17
Tvrdojevic, Mijo, Milan Vujanovic, Peter Priesching, Ferry A. Tap, Anton Starikov, Dmitry Goryntsev, and Manolis Gavaises. "Implementation of the Semi Empirical Kinetic Soot Model Within Chemistry Tabulation Framework for Efficient Emissions Predictions in Diesel Engines." Open Physics 17, no. 1 (December 31, 2019): 905–15. http://dx.doi.org/10.1515/phys-2019-0096.
Abstract:
Abstract Soot prediction for diesel engines is a very important aspect of internal combustion engine emissions research, especially nowadays with very strict emission norms. Computational Fluid Dynamics (CFD) is often used in this research and optimisation of CFD models in terms of a trade-off between accuracy and computational efficiency is essential. This is especially true in the industrial environment where good predictivity is necessary for engine optimisation, but computational power is limited. To investigate soot emissions for Diesel engines, in this work CFD is coupled with chemistry tabulation framework and semi-empirical soot model. The Flamelet Generated Manifold (FGM) combustion model precomputes chemistry using detailed calculations of the 0D homogeneous reactor and then stores the species mass fractions in the table, based on six look-up variables: pressure, temperature, mixture fraction, mixture fraction variance, progress variable and progress variable variance. Data is then retrieved during online CFD simulation, enabling fast execution times while keeping the accuracy of the direct chemistry calculation. In this work, the theory behind the model is discussed as well as implementation in commercial CFD code. Also, soot modelling in the framework of tabulated chemistry is investigated: mathematical model and implementation of the kinetic soot model on the tabulation side is described, and 0D simulation results are used for verification. Then, the model is validated using real-life engine geometry under different operating conditions, where better agreement with experimental measurements is achieved, compared to the standard implementation of the kinetic soot model on the CFD side.
18
Li, Xu, Chuanlei Yang, Yinyan Wang, Hechun Wang, Xianghuan Zu, Yongrui Sun, and Song Hu. "Compressor map regression modelling based on partial least squares." Royal Society Open Science 5, no. 8 (August 2018): 172454. http://dx.doi.org/10.1098/rsos.172454.
Abstract:
In this work, two kinds of partial least squares modelling methods are applied to predict a compressor map: one uses a power function polynomial as the basis function (PLSO), and the other uses a trigonometric function polynomial (PLSN). To demonstrate the potential capabilities of PLSO and PLSN for a typical interpolated prediction and an extrapolated prediction, they are compared with two other classical data-driven modelling methods, namely the look-up table and artificial neural network (ANN). PLSO and PLSN are also compared with each other. The results show that PLSO and PLSN have a better prediction performance than the look-up table and the ANN, especially for the extrapolated prediction. The computational time is also decreased sharply. Compared with PLSO, PLSN is characterized by a higher prediction accuracy and shorter computational time than PLSO. It is expected that PLSN could save computational time and also improve the accuracy of a thermodynamic model of a diesel engine.
19
Zhang, Wei Jiang. "The Application of Fuzzy Control in Vehicle Emission Reduction Technology." Applied Mechanics and Materials 719-720 (January 2015): 306–10. http://dx.doi.org/10.4028/www.scientific.net/amm.719-720.306.
Abstract:
In this paper, fuzzy control was applied in the technology of reducing NOx of vehicle exhaust. The calculation model of control system was obtained through theoretical derivation. The input and the output of the control system were obtained through bench test, and then established the control system table. Fulfilled the hardware installation and debugging of SCR system, DSPACE system, NOx sensor and engine system, and then the control system look-up table was be written in DSPACE /MATLAB system. It is proved that the application of fuzzy control in vehicle emission reduction is feasible through the processing and analysis of test data.
20
Guardiola, C., B. Pla, D. Blanco-Rodriguez, and L. Eriksson. "A computationally efficient Kalman filter based estimator for updating look-up tables applied to NOx estimation in diesel engines." Control Engineering Practice 21, no. 11 (November 2013): 1455–68. http://dx.doi.org/10.1016/j.conengprac.2013.06.015.
21
Leon, Vasileios, Spyridon Mouselinos, Konstantina Koliogeorgi, Sotirios Xydis, Dimitrios Soudris, and Kiamal Pekmestzi. "A TensorFlow Extension Framework for Optimized Generation of Hardware CNN Inference Engines." Technologies 8, no. 1 (January 13, 2020): 6. http://dx.doi.org/10.3390/technologies8010006.
Abstract:
The workloads of Convolutional Neural Networks (CNNs) exhibit a streaming nature that makes them attractive for reconfigurable architectures such as the Field-Programmable Gate Arrays (FPGAs), while their increased need for low-power and speed has established Application-Specific Integrated Circuit (ASIC)-based accelerators as alternative efficient solutions. During the last five years, the development of Hardware Description Language (HDL)-based CNN accelerators, either for FPGA or ASIC, has seen huge academic interest due to their high-performance and room for optimizations. Towards this direction, we propose a library-based framework, which extends TensorFlow, the well-established machine learning framework, and automatically generates high-throughput CNN inference engines for FPGAs and ASICs. The framework allows software developers to exploit the benefits of FPGA/ASIC acceleration without requiring any expertise on HDL development and low-level design. Moreover, it provides a set of optimization knobs concerning the model architecture and the inference engine generation, allowing the developer to tune the accelerator according to the requirements of the respective use case. Our framework is evaluated by optimizing the LeNet CNN model on the MNIST dataset, and implementing FPGA- and ASIC-based accelerators using the generated inference engine. The optimal FPGA-based accelerator on Zynq-7000 delivers 93% less memory footprint and 54% less Look-Up Table (LUT) utilization, and up to 10× speedup on the inference execution vs. different Graphics Processing Unit (GPU) and Central Processing Unit (CPU) implementations of the same model, in exchange for a negligible accuracy loss, i.e., 0.89%. For the same accuracy drop, the 45 nm standard-cell-based ASIC accelerator provides an implementation which operates at 520 MHz and occupies an area of 0.059 mm 2 , while the power consumption is ∼7.5 mW.
22
Jin, Li Qiang, Chuan Xue Song, and Jian Hua Li. "Intelligent Velocity Control Strategy for Electric Vehicles." Applied Mechanics and Materials 80-81 (July 2011): 1180–84. http://dx.doi.org/10.4028/www.scientific.net/amm.80-81.1180.
Abstract:
In conventional vehicles, the control of vehicle speed is achieved by changing the engine load through adjusting the acceleration pedal. However, in electric vehicles, this is achieved by controlling the target motor torque obtained from the look-up table in accordance with the position of acceleration pedal. This method is an open-loop control, with which the engine brake cannot be implemented during downhill trips. In this paper, a closed-loop control of vehicle speed for electric vehicles is proposed. The target vehicle speed is set by the acceleration pedal. The controller collects the real vehicle speed, whereas the PID controller, according to the error of the real and target vehicle speed, adjusts the motor torque in real time to realize the closed-loop speed control. Under such controlling, the motor torque can be changed correspondingly with the resistance, thus makes the driving performance of electric vehicles more identical to that of conventional vehicles.
23
Lucchini, Tommaso, Daniel Pontoni, Gianluca D’Errico, and Bart Somers. "Modeling diesel combustion with tabulated kinetics and different flame structure assumptions based on flamelet approach." International Journal of Engine Research 21, no. 1 (July 16, 2019): 89–100. http://dx.doi.org/10.1177/1468087419862945.
Abstract:
Computational fluid dynamics analysis represents a useful approach to design and develop new engine concepts and investigate advanced combustion modes. Large chemical mechanisms are required for a correct description of the combustion process, especially for the prediction of pollutant emissions. Tabulated chemistry models allow to reduce significantly the computational cost, maintaining a good accuracy. In the present work, an investigation of tabulated approaches, based on flamelet assumptions, is carried out to simulate turbulent Diesel combustion in the Spray A framework. The Approximated Diffusion Flamelet is tested under different ambient conditions and compared with Flamelet Generated Manifold, and both models are validated with Engine Combustion Network experimental data. Flame structure, combustion process and soot formation were analyzed in this work. Computed results confirm the impact of the turbulent–chemistry interaction on the ignition event. Therefore, a new look-up table concept Five-Dimensional-Flamelet Generated Manifold, that accounts for an additional dimension (strain rate), has been developed and tested, giving promising results.
24
Sun, Xiaoliang, Hu Ma, and Jing Li. "Non-geodesic winding design method for the composite shell of unequal-pole-hole solid rocket motor." Journal of Physics: Conference Series 2764, no. 1 (May 1, 2024): 012023. http://dx.doi.org/10.1088/1742-6596/2764/1/012023.
Abstract:
Abstract Advanced composite materials have the advantages of high specific strength, high specific modulus, good fatigue resistance, good shock absorption performance, and strong designability. They are widely used in the fields of national defense science and technology and civil engineering. To make a more accurate winding design of the composite shell of the non-equidistant solid rocket motor, based on the ANSYS ACP composite structure design and analysis software, this paper uses the cubic spline function method to design the fiber winding thickness of the shell head section for a solid rocket motor. The Runge-Kutta method is used to calculate the changing winding angle of the non-geodesic line, and the changing winding angle and winding thickness on the head are simulated based on the look-up table interpolation table module in ACP. Finally, the mechanical properties of the designed shell under certain internal pressure are simulated and analyzed. Through the simulation analysis of the designed engine model, it is found that the connection between the front head and the barrel section is a weak profit, and the follow-up study should reinforce this area.
25
KT, Aakash, Eric Heitz, Jonathan Dupuy, and P. J. Narayanan. "Bringing Linearly Transformed Cosines to Anisotropic GGX." Proceedings of the ACM on Computer Graphics and Interactive Techniques 5, no. 1 (May 4, 2022): 1–18. http://dx.doi.org/10.1145/3522612.
Abstract:
Linearly Transformed Cosines (LTCs) are a family of distributions that are used for real-time area-light shading thanks to their analytic integration properties. Modern game engines use an LTC approximation of the ubiquitous GGX model, but currently this approximation only exists for isotropic GGX and thus anisotropic GGX is not supported. While the higher dimensionality presents a challenge in itself, we show that several additional problems arise when fitting, post-processing, storing, and interpolating LTCs in the anisotropic case. Each of these operations must be done carefully to avoid rendering artifacts. We find robust solutions for each operation by introducing and exploiting invariance properties of LTCs. As a result, we obtain a small 84 look-up table that provides a plausible and artifact-free LTC approximation to anisotropic GGX and brings it to real-time area-light shading.
26
Brockway, Pam, and Saroj Ghoting. "Libraries at the Table for Kindergarten Readiness: Experiences and Tools to Grow On." Children and Libraries 17, no. 4 (December 2, 2019): 14. http://dx.doi.org/10.5860/cal.17.4.14.
Abstract:
“The training I received from PLYMC’s Kindergarten Readiness Workshop didn’t simply help me to understand the number of ways our libraries are striving to support school readiness, it enabled me to effectively communicate with and engage parents and caregivers as to how they can be active participants in this endeavor as well. The workshop group activities created a dialogue that allowed me to internalize what we learned from the assigned readings by coming up with and discussing the different ways learning domains can be implemented in practice.”—Marnie Alvarez, Readers’ Services Librarian, Main LibraryThe growth articulated here is the result of the Public Library of Youngstown and Mahoning County’s (PLYMC) Kindergarten Readiness Initiative. Mahoning County (OH) has a long history of supporting early literacy. After reviewing kindergarten readiness assessment results for our county, we realized we could strengthen our value in the community by articulating how we support all school readiness domains and look for ways to increase support to families who most need kindergarten readiness support.
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Tang, Yuanyuan, He Li, Yuchi Jiang, Wenwei Liang, and Jundong Zhang. "The Control-Oriented Heat Release Rate Model for a Marine Dual-Fuel Engine under All the Operating Modes and Loads." Journal of Marine Science and Engineering 11, no. 1 (January 2, 2023): 64. http://dx.doi.org/10.3390/jmse11010064.
Abstract:
An accurate model plays an important role in control strategy development of smart ships. For the control-oriented engine models, calibration by experienced personnel is key to outputting high accuracy. However, the dual-fuel engine runs in liquid fuel mode, gas fuel mode, and fuel sharing mode. It is impossible to tune a single model or a set of parameters for the dual-fuel engine under all operating modes and loads. On the basis of our experience and practice, a Wiebe-based heat release rate model is used. To make the Wiebe model available for the dual-fuel engine, the Wiebe parameters are assumed to be linear functions. The combustion beginning angle is modeled as a function of fuel quantity in liquid fuel mode and as a look-up table in gas fuel mode for all loads. The combustion duration and the combustion distribution factor are modeled as a function of fuel quantity and engine revolution both in liquid fuel mode and in gas fuel mode. In fuel sharing mode, the heat release rate is modeled as a combination of the heat release rate models in liquid fuel mode and gas fuel mode. This model is called the SL model. For a further discussion, four types of combinations in fuel sharing mode are investigated. In addition, in liquid fuel mode and gas fuel mode, the combustion duration model and the combustion distribution factor model are replaced by the Woschni/Anisits model, which was specifically used in the diesel engine. This variation of model is called the WA model. To validate our hypothesis and models, the Wiebe parameters in liquid fuel mode and gas fuel mode are given, four types of combinations and two cases of comparisons in fuel sharing model are discussed, and the engine performance is checked and analysed. Results show that for the SL model, the average RMSE is 1.45% in the liquid fuel mode, 2.22% in the gas fuel mode, and 2.53% in the fuel sharing mode. For the WA model, the RMSE of the NOx is 9.79% in liquid fuel mode and 45.20% in gas fuel mode. Its maximum error reaches −65.54%. The proposed SL model is accurate and can generate Wiebe parameters that are better than the carefully tuned parameters. The WA model is not suitable for engine models that require NOx-emission-related parameters.
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Barasa, Patrick Simiyu, Ayub Shitetswa, and Charles Kibanani Ngome. "EFFECTS OF TRANSPARENCY-FOCUSED SOCIAL ACCOUNTABILITY ACTIONS ON PUBLIC SERVICE DELIVERY IN KAKAMEGA COUNTY GOVERNMENT MINISTRIES, KENYA." IJRDO - Journal of Business Management 9, no. 6 (July 1, 2023): 1–4. http://dx.doi.org/10.53555/bm.v9i6.5751.
Abstract:
The provision of public services in the Republic of Kenya has encountered difficulties over the years. The implementation of many policies, such as performance contracts and measurement and evaluation, has not produced the desired outcomes. Therefore, it was necessary to concentrate on alternative approaches to enhance public service delivery, such as the implementation of social accountability measures. By encouraging openness through social accountability initiatives, corruption and bureaucratic inefficiencies are reduced, which enhances the delivery of services. Few studies have examined the link between the acts of social of accountability and delivery of services in Kenya, despite the fact that they are, thought to increase service delivery in the public sector. This study therefore sought to interrogate the effect of transparency-focused social accountability actions on public service delivery in Kakamega County Government Ministries, Kenya. The study was centered on Vance, Lowry, and Eggett's Accountability theory (2015). The research used a descriptive survey research approach. The employees from different ministries, county assembly members, as well as chief officers, who take part in public decision-making processes, made up the target population. A population of 1,904 persons was targeted. Accordingly, using Krejcie and Morgan (1970) table, a sample size of 322 was obtained. To analyse the quantitative data, the researcher employed the Statistical Package for Social Sciences. Content analysis was, used to look at qualitative data. The research instruments’ validity was certified by the experts in the area of study, while reliability of the research instruments was determined by use of Cronbach's alpha coefficient. This was meant to check on the internal consistency of the research instruments. A standardized questionnaire and interviews was used to collect the data, which was then analyzed using descriptive and inferential statistics and presented using tables. For this investigation, a multivariate regression analysis was, used. The findings revealed that transparency focused (β=.652, p<.05) had a positive significant effect on service delivery and accounted for 41.7%. The employees of Kakamega County may gain from this research because it will allow them to engage in more discussions with the county by engaging in advisory boards, project implementation, and project feasibility analysis, all of which can enhance the county's provision of public services.
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Wu, Hsiu-Ming, and Reza Tafreshi. "Digital fuzzy sliding-mode control for a linear parameter-varying air–fuel ratio system." Advances in Mechanical Engineering 11, no. 1 (January 2019): 168781401882210. http://dx.doi.org/10.1177/1687814018822104.
Abstract:
Air–fuel ratio is a key factor for the minimization of the harmful pollutant emissions and maximization of fuel economy. However, a big challenge for air–fuel ratio control is a large time-varying delay existing in spark ignition engines. In this article, a digital fuzzy sliding-mode controller is proposed to control a linear parameter-varying sampled-data air–fuel ratio system. First, the Pade first-order technique is utilized to approximate the time-varying delay. The resultant system—a linear parameter-varying continuous-time air–fuel ratio system with unstable internal dynamics—is then discretized to a linear parameter-varying sampled-data air–fuel ratio system appropriate for a discrete-time control approach. Based on the linear parameter-varying sampled-data air–fuel ratio system, a stable sliding surface with a desired tracking error dynamics is presented. Two input scaling factors and one output scaling factor are determined for the proposed digital fuzzy sliding-mode controller. Then, the fuzzy inference is executed through a look-up table to stabilize the sliding surface into a convex set, and then make the tracking error possess uniformly ultimately bounded performance. The overall system stability is verified by Lyapunov’s stability criteria. Finally, the simulation results demonstrate the feasibility, effectiveness, and robustness of the proposed control scheme under different operating conditions and show the superiority of the proposed approach performance compared to the baseline controller.
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Wei, Xin, Wenchao Liu, Lei Chen, Long Ma, He Chen, and Yin Zhuang. "FPGA-Based Hybrid-Type Implementation of Quantized Neural Networks for Remote Sensing Applications." Sensors 19, no. 4 (February 22, 2019): 924. http://dx.doi.org/10.3390/s19040924.
Abstract:
Recently, extensive convolutional neural network (CNN)-based methods have been used in remote sensing applications, such as object detection and classification, and have achieved significant improvements in performance. Furthermore, there are a lot of hardware implementation demands for remote sensing real-time processing applications. However, the operation and storage processes in floating-point models hinder the deployment of networks in hardware implements with limited resource and power budgets, such as field-programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs). To solve this problem, this paper focuses on optimizing the hardware design of CNN with low bit-width integers by quantization. First, a symmetric quantization scheme-based hybrid-type inference method was proposed, which uses the low bit-width integer to replace floating-point precision. Then, a training approach for the quantized network is introduced to reduce accuracy degradation. Finally, a processing engine (PE) with a low bit-width is proposed to optimize the hardware design of FPGA for remote sensing image classification. Besides, a fused-layer PE is also presented for state-of-the-art CNNs equipped with Batch-Normalization and LeakyRelu. The experiments performed on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset using a graphics processing unit (GPU) demonstrate that the accuracy of 8-bit quantized model drops by about 1%, which is an acceptable accuracy loss. The accuracy result tested on FPGA is consistent with that of GPU. As for the resource consumptions of FPGA, the Look Up Table (LUT), Flip-flop (FF), Digital Signal Processor (DSP), and Block Random Access Memory (BRAM) are reduced by 46.21%, 43.84%, 45%, and 51%, respectively, compared with that of floating-point implementation.
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Giovanni, Giardiello, de Nola Francesco, Ghezzi Giuliana, Gimelli Alfredo, Iossa Raffaele, Langella Giuseppe, and Sessa Bernardo. "Model and transient Control strategy design of an Organic Rankine Cycle Plant for waste heat recovery of an Internal Combustion Engine." Journal of Physics: Conference Series 2385, no. 1 (December 1, 2022): 012118. http://dx.doi.org/10.1088/1742-6596/2385/1/012118.
Abstract:
Abstract The multi-sources hybrid polygeneration energy systems are of great interest and topicality as they are one of the most promising technologies in the European’s Green Deal panorama, with the aim of serving users with electrical and thermal energy using a single plant powered by one or more energy sources. In the waste heat recovery field Organic Rankine Cycle (ORC) power plants are becoming increasingly popular, especially for exploiting medium and low temperature heat sources as a micro-small scale power plant. However, the development and diffusion of this technology is still limited due to the high costs and consequently prototype development and experimental assessment of performance is very poor, especially for non-stationary systems. In this work the modelling and validation of a micro-scale waste heat recovery (WHR) plant coupled with a control system is presented. An ORC plant has been modelled through a map-based model approach for the piston pump and the scroll expander while the pipes and the heat exchangers through a 1D thermo-fluid dynamic approach. A preliminary comparison was made between some numerical quantities of the modelled plant and the same experimental quantities in 61 different operating conditions, showing an average error of 50.1%. The model has been calibrated using a vector optimization technique: two calibration parameters of the heat exchangers were calibrated with a genetic algorithm (MOGA II) by reducing the error of 5 quantities obtained from the model with the respective experimental quantities in 15 different operating conditions. The remaining 46 operating conditions were used to evaluate the calibrated model, showing an average error of 3%. Furthermore, in order to provide for the use of the system coupled to highly variable heat sources, such as the exhaust gases of an internal combustion engine, a control strategy has been designed to perform two tasks: leading the ORC performance where the efficiency is higher, acting on the pump speed through a map-based control, implemented by a look-up table control, and protecting the organic fluid from damage caused by high working temperatures through a bypass control system with a PI control, depending on the proportional and integral gains. In order to verify the control strategy behaviour at different thermal transient inputs, a set of simulations has been run, showing a robust and stable manner preserving the organic fluid properties and limiting the superheated steam at expander inlet.
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Yang, Ye, Youtong Zhang, Jingyi Tian, and Si Zhang. "Research on a Plug-In Hybrid Electric Bus Energy Management Strategy Considering Drivability." Energies 11, no. 8 (August 20, 2018): 2177. http://dx.doi.org/10.3390/en11082177.
Abstract:
Plug-in hybrid electric buses (PHEBs) is some of the most promising products to address air pollution and the energy crisis. Considering the switching between different working modes often bring aboutsudden changes of the torque and the speed of different power sources, which may lead to the instability of the power output and affect the driving performance and ride comfort, it is of great significance to develop a real-time optimal energy management strategy for PHEBs to achieve the optimization of fuel economy and drivability. In this study, the proposed strategy includes an offline part and an online part. In the offline part, firstly, the energy conversion coefficient s(t) is optimized by linear weight particle swarm optimization algorithm (LinWPSO), then, the optimization results of s(t) are converted into a 2-dimensional look-up table. Secondly, combined with three typical driving cycle conditions, the gear-shifting correction and mode switching boundary parameters that affect the drivabilityof the vehicle are extracted by dynamic programming (DP) algorithm. In the online part, combined with the s(t), the gear-shifting correction and mode switching boundary parameters which are obtained through offline optimization, the real-time energy management strategy is proposed to solve the trade-off problem between minimizing the fuel consumption and improving the drivability and riding comfort. Finally, the proposed strategy is verified with simulation, the results show that the proposed strategy can guarantee the engine and the electric motor (EM) work in the high-efficiency area with optimal energy distribution while keeping drivability in the variation of driving circle. The overall performance is improved by 18.54% compared with the rule-based control strategy. The proposed strategy may provide theoretical support for the optimal control of PHEB.
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Cipriano, Brandon Jamos, Rovinna Janel Cruzate, Sheryl Diokno, Frederick Samonte, Luis Jarod de Luna, Lew Andrew Tria, Karl Vergel, Paul Rodgers, Carl Michael Odulio, and Ernesto Abaya. "Modeling and analysis of the voyage cycle for ferryboat electrification." Maritime Technology and Research 5, no. 3 (February 9, 2023): 261999. http://dx.doi.org/10.33175/mtr.2023.261999.
Abstract:
Voyage cycle modeling provides an estimation of the battery energy requirements in preparation for the electrification of passenger ships. In this study, the objectives are to model the voyage cycle of a public transportation ferry and to determine the appropriate battery storage capacity in preparation for ferry electrification. Pasig River Ferry Service (PRFS), located in Metro Manila, Philippines, was used to model a voyage cycle for ferryboat electrification. Speed and route characteristic data were gathered during the operations of the ferry through a surveyor equipped with a GPS logger. The voyage characteristics gathered, ferry specifications, and diesel engine look-up table were used as inputs to develop a Simulink model that provides the estimated fuel consumption and the equivalent power consumption of the ferry in the case of electrification. The fuel consumption estimate was validated by comparing it to the fuel consumed during actual operation. Based on initial results, the fuel consumption estimates have percentage errors that vary from 2.25 to 12.94 % compared to the actual recorded fuel consumption during operations. The instantaneous power consumption from the voyage cycle Simulink model was used as an input to battery discharge simulations to evaluate the target battery design of the equivalent electric ferry system. Using the methodology of this study, the battery configuration and capacity were determined and evaluated for a single roundtrip voyage of the passenger boat. Highlights Voyage Cycle modeling can provide an overview of the performance of a ferry Fuel and energy consumption can be estimated from the voyage cycle Battery discharge simulation is a method used to verify the battery system design Voyage Cycle Modeling is an initial step for existing boat operators in determining the energy requirements prior to electrification
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Mehmeti, Ermira. "Quest for Statehood: Kosovo’s Plea to Join International Organizations." European Journal of Social Sciences Education and Research 11, no. 2 (June 10, 2017): 370. http://dx.doi.org/10.26417/ejser.v11i2.p370-378.
Abstract:
The State represents a central concept and a basic subject of international law. In order to function and engage in treaties and relations with other states in a growing globalized world, the State must be accepted and treated as independent by other states. But independence alone is not enough. Declaring independence is typically a unilateral act undertaken by one entity. Hence, there are states in the world today that are independent; however, their international subjectivity is not recognized. This makes their position and ability to engage in the international sphere more complex. As a result, authorities look into ways of bypassing formal recognition. Joining international organizations becomes one alternative. This article explores the quest of Kosovo to join international organizations as a way to secure recognition and statehood. It begins with the United Nations, and briefly analyses the diplomatic efforts of Kosovar governments to accede. The focus of this article however, will be more specifically on Kosovo’s application to join UNESCO, the United Nations’ cultural organization, the Council of Europe and international sports federations, for this process will shed light on several important legal and political aspects of recognition: the application procedure, the political interests of states, the lobbying and securing of states’ support in an entity’s bid to obtain a seat at the organization. Membership in UNESCO is rightfully seen as a gateway to reach to a seat at the United Nations, while bypassing unilateral recognitions granted by states individually. While membership in international organizations will not imply recognition of international subjectivity for a new entity, in practical terms, it offers to achieve what recognition promises. Kosovo has been able to sit at the same table with its regional counterparts and has been able to participate and share in various regional initiatives. As an initial phase of normalization of relations with Serbia, this represents a solid step forward. At a later stage, it could serve as an incentive, or even better as a catalyst to speed up securing full-fledged statehood.
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Friedrich, Bettina, and Oliver John Mason. "“What is the score?” A review of football-based public mental health interventions." Journal of Public Mental Health 16, no. 4 (December 18, 2017): 144–58. http://dx.doi.org/10.1108/jpmh-03-2017-0011.
Abstract:
Purpose Football exercise as an intervention for people with severe mental health problems has seen an increasing interest in the past years. To date, there is, however, no comprehensive review of the empirical evidence regarding the effectiveness of these interventions. In this review, the authors have comprised the research findings from the peer-review literature as well as the theoretical approaches to football exercise as an adjunct treatment. This overview will be informative to everybody who is planning to develop a football intervention for this population as well as to the people who are preparing evaluation studies that measure the effectiveness of such interventions. The paper aims to discuss these issues. Design/methodology/approach The authors identified research papers in the peer-review literature that feature empirical findings on “football interventions” that aim at improving mental and/or physical well-being in participants with mental health problems. The authors are using the term “football intervention” here in the sense that the participants actively took part in football exercise, so the authors excluded studies in which the participants only watched football or used football as a metaphor to discuss mental health problems. In a table, the authors indicate the definition of the target group, targeted outcomes, measured outcomes, form and frequency of the intervention as well as the research method(s). Findings The authors identified 16 studies on 15 projects. The majority of studies were qualitative and had positive findings in which the participants reported increased well-being and connectedness, elevation of symptoms and improved physical well-being. The outcomes of the quantitative studies, however, were mixed with some results suggesting that not all intended goals were achieved. There seems to be a need for more quantitative studies to triangulate the qualitative findings. Interestingly, most interventions take place in the UK. Many studies fail to give detailed methodological information and often the aims of the interventions are vague or not stated at all. Research limitations/implications Due to the heterogeneity of the studies and relative scarcity of evaluation projects on football interventions for people with mental health problems, the authors could not conduct an in-depth systematic review. Furthermore, the information on methods was often unsatisfying and despite efforts to get more detailed input from the authors of cited papers, those gaps could not always be filled. Instead of coming up with a crystal-clear summary of whether and how football interventions work for everybody, topics were identified that need to be addressed in the planning of interventions, in evaluation studies, in implementation efforts and in the theoretical discourse. Practical implications This paper constitutes a helpful overview for everybody who is interested in the theoretical background of football interventions for people with mental health problems, for people who are planning to develop respective interventions, for researchers who engage in evaluation projects that look into the effectiveness of football interventions (or similar exercise interventions) as well as for the people who are interested in how football interventions can be implemented. This paper is likely to make a contribution to the advancement of alternative exercise interventions that aim at improving mental, physical and social health in people with mental health problems. Social implications This paper will help putting the topic of football interventions (and similar, alternative exercise interventions) further up on the public health agenda by providing an overview of the empirical evidence at hand and by specifying advantages of the approach as well as pointing out actions that need to be taken to make football a recognised, evidence based and viable option for adjunct mental health treatment that is attractive to potential participants as well as funders as well as to the potential participants. Originality/value There is no comprehensive summary to date that provides a (reasonably) systematic overview of empirical findings for football interventions for people with MH problems. Furthermore, the literature on the theoretical background of these interventions has been somewhat patchy and heterogonous. This paper aims at filling both these gaps and identifies the issues that need to be covered in the planning of respective interventions and evaluations. This paper will be useful to everybody who is developing football interventions (or similar alternative adjunct exercise interventions), who is conducting evaluation research in this area and who is interested in the implementation of football interventions.
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Srivastava, Vivek, Utkarsh Sharma, Joschka Schaub, and Stefan Pischinger. "Adaptive control concepts using radial basis functions and a Kalman filter for embedded control applications." International Journal of Engine Research, August 18, 2023. http://dx.doi.org/10.1177/14680874231192896.
Abstract:
Look-up tables or semi-physical models are used in engine control application to enhance the transient control performance. However, the calibration of these look-up tables and/or semi-physical models is highly data dependent, requires significant calibration effort, and does not account for effects such as hardware aging, drifts, fuel variations, etc. To address these challenges, this paper presents a generic adaptive control concept for real-time engine control applications. The boundary conditions for the operation on a state-of-the-art engine control unit (ECU) are considered and Radial Basis Function (RBF)-based neural networks are identified for the approximation of non-linear models. To ensure optimal convergence and un-susceptibility to signal noise, a Kalman filter (KF) is exploited for training the RBF network and a modified approximation is derived in this work. The derived KF approximation shows ∼30% better training performance in comparison to the approximation without variable noise consideration. The developed control concept is validated on an engine test bench and a demonstrator vehicle using a Rapid Control Prototyping (RCP) system. The potential of the developed control concept to ensure optimal control response and robustness has been demonstrated.
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Siddique, Ali, Mang I. Vai, and Sio Hang Pun. "A low cost neuromorphic learning engine based on a high performance supervised SNN learning algorithm." Scientific Reports 13, no. 1 (April 18, 2023). http://dx.doi.org/10.1038/s41598-023-32120-7.
Abstract:
AbstractSpiking neural networks (SNNs) are more energy- and resource-efficient than artificial neural networks (ANNs). However, supervised SNN learning is a challenging task due to non-differentiability of spikes and computation of complex terms. Moreover, the design of SNN learning engines is not an easy task due to limited hardware resources and tight energy constraints. In this article, a novel hardware-efficient SNN back-propagation scheme that offers fast convergence is proposed. The learning scheme does not require any complex operation such as error normalization and weight-threshold balancing, and can achieve an accuracy of around 97.5% on MNIST dataset using only 158,800 synapses. The multiplier-less inference engine trained using the proposed hard sigmoid SNN training (HaSiST) scheme can operate at a frequency of 135 MHz and consumes only 1.03 slice registers per synapse, 2.8 slice look-up tables, and can infer about 0.03$$\times {\varvec{10}}^{\varvec{9}}$$ × 10 9 features in a second, equivalent to 9.44 giga synaptic operations per second (GSOPS). The article also presents a high-speed, cost-efficient SNN training engine that consumes only 2.63 slice registers per synapse, 37.84 slice look-up tables per synapse, and can operate at a maximum computational frequency of around 50 MHz on a Virtex 6 FPGA.
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Fontanesi, Stefano, Fabiyan Angikath Shamsudheen, Edwing Grajales Gonzalez, S. Mani Sarathy, Fabio Berni, Alessandro d’Adamo, Massimo Borghi, and Sebastiano Breda. "Impact of fuel surrogate formulation on the prediction of knock statistics in a single cylinder GDI engine." International Journal of Engine Research, August 31, 2023. http://dx.doi.org/10.1177/14680874231195742.
Abstract:
The statistical tendency of an optically accessible single-cylinder direct-injection spark-ignition engine to undergo borderline/medium knocking combustion is investigated using 3D-CFD. Focus is made on the role of fuel surrogate formulation for the characterization of anti-knock quality and flame speed of the actual fuel. An in-house methodology is used to design surrogates able to emulate laminar flame speed and autoignition delay times of the injected fuel. Two different surrogates, characterized by increasing level of complexity, are compared. The most complex one (six components) improves the representation of the real fuel, highlighting the crucial role of accurate fuel kinetics to predict flame propagation and unburnt mixture reactivity. A devoted chemical mechanism including the oxidation pathways for all the species in the surrogate is also purposely developed for the current analysis. Knock is investigated using a proprietary statistical knock model (GruMo-UNIMORE Statistical Knock Model, GK-PDF), which can infer the probability of knocking events within a RANS formalism. Predicted statistical distributions are compared to measured counterparts. The proposed numerical/experimental comparison demonstrates the possibility to efficiently integrate complex-chemistry driven information in 3D-CFD combustion simulations without online solving chemical reactions: a combination of laminar flame speed correlations, ignition delay look-up tables, and a statistics-based knock model is adopted to estimate the percentage of knocking cycles in a GDI engine while limiting the computational cost of the simulations.
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Min, Kyunghan, Haksu Kim, Manbae Han, and Myoungho Sunwoo. "Set-Point Adaptation Strategy of Air Systems of Light-Duty Diesel Engines for NOx Emission Reduction Under Acceleration Conditions." Journal of Engineering for Gas Turbines and Power 140, no. 7 (April 10, 2018). http://dx.doi.org/10.1115/1.4038543.
Abstract:
Modern diesel engines equip the exhaust gas recirculation (EGR) system because it can suppress NOx emissions effectively. However, since a large amount of exhaust gas might cause the degradation of drivability, the control strategy of EGR system is crucial. The conventional control structure of the EGR system uses the mass air flow (MAF) as a control indicator, and its set-point is determined from the well-calibrated look-up table (LUT). However, this control structure cannot guarantee the optimal engine performance during acceleration operating conditions because the MAF set-point is calibrated at steady operating conditions. In order to optimize the engine performance with regard to NOx emission and drivability, an optimization algorithm in a function of the intake oxygen fraction (IOF) is proposed because the IOF directly affects the combustion and engine emissions. Using the NOx and drivability models, the cost function for the performance optimization is designed and the optimal value of the IOF is determined. Then, the MAF set-point is adjusted to trace the optimal IOF under engine acceleration conditions. The proposed algorithm is validated through scheduled engine speeds and loads to simulate the extra-urban driving cycle of the European driving cycle. As validation results, the MAF is controlled to trace the optimal IOF from the optimization method. Consequently, the NOx emission is substantially reduced during acceleration operating conditions without the degradation of drivability.
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Lee, Hyunjun, Manbae Han, and Myoungho Sunwoo. "Cylinder Pressure Information-Based Postinjection Timing Control for Aftertreatment System Regeneration in a Diesel Engine—Part I: Derivation of Control Parameter." Journal of Engineering for Gas Turbines and Power 138, no. 8 (March 15, 2016). http://dx.doi.org/10.1115/1.4032540.
Abstract:
The implementation of aftertreatment systems in passenger car diesel engines, such as a lean NOx trap (LNT) and a diesel particulate filter (DPF), requires an in-cylinder postinjection (POI) for a periodic regeneration of those aftertreatment systems to consistently reduce tail-pipe emissions. Although the combustion and emission characteristics are changed from the normal engine operating conditions due to the POI, POI is generally applied with a look-up table (LUT) based feedforward control because of its cost effectiveness and easy implementation into the engine management system (EMS). However, the LUT-based POI control necessities tremendous calibration work to find the optimal timing to supply high exhaust gas temperature or enough reductants such as carbon monoxide (CO) and hydrocarbon to regenerate the aftertreatment systems while maintaining low engine-out smoke emissions. To solve this problem, we propose a novel combustion analysis method based on the cylinder pressure information. This method investigates the relation between the POI timing with the exhaust emissions and compensates the combustion phase shift occurred by the engine operating condition changes, such as the engine speed and injection quantity. A burning rate of fuel after a location of the rate of heat release maximum (BRaLoROHRmax) was derived from the combustion analysis. A mass fraction burned X% after a location of the rate of heat release maximum (MFBXaLoROHRmax) was determined using the BRaLoROHRmax and main injection (MI) quantity. Nonlinear characteristics of the exhaust emissions according to POI timing variations and the combustion phase shift due to the engine operating condition changes can be easily analyzed and compensated in terms of the proposed MFBXaLoROHRmax domain. The proposed method successfully evaluated its utility through the engine experiments for the LNT and DPF regeneration.
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A. S. Franco, Ramon, Pedro Loures Alzamora, Janaína Guiginski, Evandro L. T. P. Cunha, Tereza Bernardes, Juan F. Galindo, Luana Passos, et al. "Covid Data Analytics Repository: An interdisciplinary look into the COVID-19 pandemic in Brazil." Journal of Information and Data Management 13, no. 1 (August 15, 2022). http://dx.doi.org/10.5753/jidm.2022.2266.
Abstract:
This article describes the construction and deployment of the Covid Data Analytics Repository, a source for interdisciplinary studies about the impact of the COVID-19 pandemic in Brazil. We collected different types of data from official (IBGE, DATASUS) and non-official (Brasil.IO) sources, online social networks (Instagram, Twitter), and from a search engine analysis tool (Google Trends). We used these data to perform investigations aimed to understand the impacts of COVID-19 in the country, from economics to social behavior. At the moment of publication of this article, our repository contains 1,508 documents, classified into two main types: (i) databases and tables downloaded from the aforementioned sources; and (ii) papers, reports, maps and graphs resulting from the analyses that we performed. As a means to allow reproducibility and foster follow-up studies, we released our repository for public use.
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Park, Yeongseop, Inseok Park, Joowon Lee, Kyunghan Min, and Myoungho Sunwoo. "Nonlinear Compensators of Exhaust Gas Recirculation and Variable Geometry Turbocharger Systems using Air Path Models for a CRDI Diesel Engine." Journal of Engineering for Gas Turbines and Power 136, no. 4 (December 19, 2013). http://dx.doi.org/10.1115/1.4026075.
Abstract:
This paper investigates the design of model-based feedforward compensators for exhaust gas recirculation (EGR) and variable geometry turbocharger (VGT) systems using air path models for a common-rail direct injection (CRDI) diesel engine to cope with the nonlinear control problem. The model-based feedforward compensators generate set-positions of the EGR valve and the VGT vane to track the desired mass air flow (MAF) and manifold absolute pressure (MAP) with consideration of the current engine operating conditions. In the best case, the rising time to reach 90% of the MAF set-point was reduced by 69.8% compared with the look-up table based feedforward compensators.
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Muhson, Ali. "Penerapan Logika Fuzzy Dalam Pemodelan Perkiraan Tingkat Inflasi Di Indonesia." Jurnal Ekonomi dan Pendidikan 4, no. 2 (February 29, 2012). http://dx.doi.org/10.21831/jep.v4i2.612.
Abstract:
Modeling for inflation rate in Indonesia was done by some researcher with conventional model. The conventional model can not be applied if the data are linguistic variables. Fuzzy system can be used to overcome the weak of this method. The goal of this research is to establish the model for forecasting inflation rate in Indonesia based on fuzzy time series data. In this research, forecasting inflation rate use table look up scheme method based on multivariate fuzzy time series data. This research is done by the following steps: 1) determine input-output data; 2) determine fuzzification for input-output data; 3) determine fuzzy rules base by table lookup scheme method; 4) construct fuzzy inference engine; 5) construct defuzzification; 6) construct fuzzy system for modeling inflation rate in Indonesia; 7) determine validation for model used MSE criteria. The results of this research are 1) we develop 8 fuzzy models; 2) The model with Gaussian membership function, minimum inference engine, 25 fuzzy rules has minimum MSE value, 5.5671. Therefore this model can be used to predict inflation rate in Indonesia based on inflation previously , credit interest rate, money supply, gross national product and exchange rate of Rupiah.
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Lee, Hyunjun, Jaesik Shin, Manbae Han, and Myoungho Sunwoo. "Cylinder Pressure Information-Based Postinjection Timing Control for Aftertreatment System Regeneration in a Diesel Engine—Part II: Active Diesel Particulate Filter Regeneration." Journal of Engineering for Gas Turbines and Power 138, no. 8 (March 15, 2016). http://dx.doi.org/10.1115/1.4032541.
Abstract:
The successful utilization of a diesel particulate filter (DPF) to reduce particulate matter (PM) in a passenger car diesel engine necessitates a periodic regeneration of the DPF catalyst without deterioration of the drivability and emission control performance. For successful active DPF regeneration, the exhaust gas temperature should be over 500 °C to oxidize the soot loaded in the DPF. Previous research increased the exhaust gas temperature by applying early and late post fuel injection with a look-up table (LUT) based feedforward control implemented into the engine management system (EMS). However, this method requires enormous calibration work to find the optimal timing and quantity of the main, early, and late post fuel injection with less certainty of accurate torque control. To address this issue, we propose a cylinder pressure based multiple fuel injection (MFI) control method for active DPF regeneration. The feedback control of the indicated mean effective pressure (IMEP), lambda, and DPF upstream temperature was applied to precisely control the injection quantity of the main, early, and late post fuel injection. To determine their fuel injection timings, a mass fraction burned 60% after location of the rate of heat release maximum (MFB60aLoROHRmax) was proposed based on the cylinder pressure information. The proposed control method was implemented in an in-house EMS and validated at several engine operating conditions. During the regeneration period, the exhaust gas temperature tracked the desired temperature, and the engine torque fluctuation was minimized with minimal PM and NOx emissions.
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Güner, Erdoğan, Aliriza Kaleli, Kadir Bakirci, and Mehmet Akif Ceviz. "Development of optimal diesel injection strategy based on the prediction of performance and emissions using deep neural network." International Journal of Engine Research, November 22, 2021, 146808742110577. http://dx.doi.org/10.1177/14680874211057756.
Abstract:
This study aims to determine the optimal injection strategy by predicting the performance and exhaust emission parameters of a four-cylinder CRDI engine under several operating conditions. The experimental determination procedure is challenging and expensive calibration task since it requires a high number of tests. Many studies have focused on a limited level of parameters. In this study, design of experiments technique and deep neural network (DNN) modeling are used together. The experimental data set for the model is created using Taguchi L16 and L32 orthogonal arrays. The DNN model is developed to predict [Formula: see text], [Formula: see text], HC, and CO emissions with speed, torque, injection timings and fuel quantities of each injection called as pilot1, pilot2, main, and post. In this way, it has become possible to evaluate the effects of a larger number of operating parameters in a wide range than the literature. The developed DNN model predicts the [Formula: see text], [Formula: see text], HC, and CO with R2 0.939, 0.943, 0.963, and 0.966, respectively. Additionally, RMSE and MAE values for the model are between 0.024 and 0.048. The proposed method compared with the conventional look-up table method performs better in reducing the complexity and cost of experiments and exploration of the effects of injection parameters on engine emission and performance characteristics in a wide engine operating range. In conclusion, until 2300 rpm at specified torque (90 Nm), it is found that 70% of fuel quantity should inject in main injection to minimize [Formula: see text] and [Formula: see text] emissions. The post injection quantity should be increased by reducing the amount of main injection from this operating condition on. Furthermore, it is observed that the ratios of pilot injection durations do not change with increasing engine speed, but quantity of first pilot injection is more than that of second pilot injection.
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Oh, Junhyeong, Kyunghan Min, Manbae Han, and Myoungho Sunwoo. "Fault Management System of LP-EGR Using In-Cylinder Pressure Information in Light-Duty Diesel Engines." Journal of Engineering for Gas Turbines and Power 140, no. 4 (November 7, 2017). http://dx.doi.org/10.1115/1.4038078.
Abstract:
Particulate matters (PM) accumulation through a low-pressure exhaust gas recirculation (LP-EGR) path may hinder to obtain the desired LP-EGR rate and thus causes an increase of nitrogen oxides (NOx). The degree of lack of the LP-EGR rate should be detected, i.e., an LP-EGR fault, and a remedy to compensate for the lack of LP-EGR rate should be a mandate to suppress NOx emission, i.e., a fault management. In order to accomplish those objectives, this paper proposes an LP-EGR fault management system, which consists of a fault diagnosis algorithm, fault-tolerant control algorithm, and an LP-EGR rate model. The model applies a combustion parameter derived from in-cylinder pressure information to the conventional orifice valve model. Consequently, the LP-EGR rate estimation was improved to the maximum error of 2.38% and root-mean-square-error (RMSE) of 1.34% at various operating conditions even under the fault condition compared to that of the conventional model with the maximum error of 7.46% and RMSE of 5.39%. Using this LP-EGR rate model as a virtual sensor, the fault diagnosis algorithm determines an LP-EGR fault state. Based on the state, the fault-tolerant control determines whether or not to generate the offset of the exhaust throttle valve (ETV) position. This offset combines with the look-up table (LUT)-based feedforward controller to control an LP-EGR rate. As a result of real-time verification of the fault management system in the fault condition, the NOx emission decreased by up to about 15%.
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Ezeh, Christopher Uche, Ogbonnaya Igwe, Mensah Yaw Asare, Dominic C. Ndulue, Romanus U. Ayadiuno, and Kwasi Preko. "A review of soil erosion modeling in Nigeria using the Revised Universal Soil Loss Equation model." Agrosystems, Geosciences & Environment 7, no. 1 (February 6, 2024). http://dx.doi.org/10.1002/agg2.20471.
Abstract:
AbstractSoil erosion is a severe soil degradation problem that endangers the actualization of Sustainable Development Goals. It affects agricultural production by reducing soil fertility via topsoil translocation, leading to soil quality deterioration. A review of soil erosion modeling using the Revised Universal Soil Loss Equation (RUSLE) model shows that Nigeria lags behind other developing countries like Ethiopia despite the massive improvements provided by remote sensing and geographic information system (GIS) technologies. Fewer than 50 articles were found on the Google Scholar search engine that used the RUSLE model for empirical studies on soil erosion. Only four research articles were found on the ScienceDirect website. Additionally, there were differences in the findings from studies across Nigeria. Such disparities were due to differences in the approaches used to estimate key factors in the RUSLE model. Therefore, we recommend that the Ministries of Agriculture and Environment take soil erosion research seriously by adopting proactive soil conservation and management measures. Ensemble models can be used including machine learning approaches rather than focusing mainly on structural intervention. In addition, there should be a harmonized look‐up table for the cover management factor and conservation practices factor that fairly represent the various ecoclimatic regions. The limitations to the model's use are highlighted, and a way forward is suggested.
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"Decision support for agricultural water management." Issue 3 14, no. 3 (April 30, 2013): 255–63. http://dx.doi.org/10.30955/gnj.000887.
Abstract:
Irrigation water use is the major pressure limiting the availability of fresh water resources in the
Mediterranean. Efficient irrigation scheduling programs (IRSPs) are able to reduce water
consumption; however, their selection and placement in large agricultural landscapes depend on
location specific characteristics and economic indicators. Towards this end, a novel and efficient
Decision Support Tool (DST) is developed in MATLAB-programming, able to assess the
effectiveness of different IRSPs in reducing total agricultural water use at the catchment scale along
with their impact on crop yields. The DST integrates a look-up table with data on irrigation water
amounts and crop yields at different locations within a catchment, populated by a hydrological and
crop growth estimator: the process-based SWAT model, into a multi-objective Genetic Algorithm,
which serves as the optimization engine for the allocation of measures across the agricultural land.
The optimization scheme leads rapidly to the optimal trade-off frontier between the conflicting
objectives providing spatial allocations of IRSPs. The tool was implemented in the Ali Efenti
catchment demonstrating optimal solutions that could save more than 10% of water by reducing
cotton yields less than 5% from the baseline. The study highlights the potential of the tool to assist in
the development of cost-effective water saving plans at the catchment level in order to reduce the
risk of desertification in intensively cultivated areas.
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Wulff, Jörg, Anne Paul, Claus Maximilian Bäcker, Kilian‐Simon Baumann, Johannes Niklas Esser, Benjamin Koska, Beate Timmermann, Nico Gerd Verbeek, and Christian Bäumer. "Consistency of Faraday cup and ionization chamber dosimetry of proton fields and the role of nuclear interactions." Medical Physics, November 22, 2023. http://dx.doi.org/10.1002/mp.16819.
Abstract:
AbstractBackgroundA Faraday cup (FC) facilitates a quite clean measurement of the proton fluence emerging from clinical spot‐scanning nozzles with narrow pencil‐beams. The utilization of FCs appears to be an attractive option for high dose rate delivery modes and the source models of Monte‐Carlo (MC) dose engines. However, previous studies revealed discrepancies of 3%–6% between reference dosimetry with ionization chambers (ICs) and FC‐based dosimetry. This has prevented the widespread use of FCs for dosimetry in proton therapy.PurposeThe current study aims at bridging the gap between FC dosimetry and IC dosimetry of proton fields delivered with spot‐scanning treatment heads. Particularly, a novel method to evaluate FC measurements is introduced.MethodsA consistency check is formulated, which makes use of the energy balance and the reciprocity theorem. The measurement data comprise central‐axis depth distributions of the absorbed dose of quasi‐monochromatic fields with a width of about 28.5 cm and FC measurements of the reciprocal fields with a single spot. These data are complemented by a look‐up of energy‐range tables, the average Q‐value of transmutations, and the escape energy carried away by neutrons and photons. The latter data are computed by MC simulations, which in turn are validated with measurements of the distal dose tail and neutron out‐of‐field doses. For comparison, the conventional approach of FC evaluation is performed, which computes absorbed dose from the product of fluence and stopping power. The results from the FC measurements are compared with the standard dosimetry protocols and improved reference dosimetry methods.ResultsThe deviation between the conventional FC‐based dosimetry and the IC‐based one according to standard dosimetry protocols was −4.7 (± 3.3)% for a 100 MeV field and −3.6 (±3.5)% for 200 MeV, thereby agreeing within the reported uncertainties. The deviations could be reduced to −4.0 (± 2.9)% and −3.0 (± 3.1)% by adopting state‐of‐the‐art reference dosimetry methods. The alternative approach using the energy balance gave deviations of only −1.9% (100 MeV) and −2.6% (200 MeV) using state‐of‐the‐art dosimetry. The standard uncertainty of this novel approach was estimated to be about 2%.ConclusionsAn alternative concept has been established to determine the absorbed dose of monoenergetic proton fields with an FC. It eliminates the strong dependence of the conventional FC‐based approach on the MC simulation of the stopping‐power and of the secondary ions, which according to the study at hand is the major contributor to the underestimation of the absorbed dose. Some contributions to the uncertainty of the novel approach could potentially be reduced in future studies. This would allow for accurate consistency tests of conventional dosimetry procedures.
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ten Bosch, Olav, Edwin de Jonge, Henk Laloli, and Christine Laaboudi-Spoiden. "FAIR Digital Objects in Official Statistics." Research Ideas and Outcomes 8 (October 12, 2022). http://dx.doi.org/10.3897/rio.8.e94485.
Abstract:
Introduction*1 Statistical offices on national and international scale provide statistics on demography, labour, income, society, economy, environment and other domains. Their collective output is usually referred to as ‘Official Statistics’. These offices have a long tradition of publishing data fairly and open, which is often part of their mission statement. For decades they have been providing websites with articles, press releases, graphs and tables of data for free, for research, for policy-making, and for common understanding. However, for users it often is not so easy to find the data needed, to (re-)use it in data-driven work or to refer to the right (sub)set of data in a sustainable way. Therefore, in this article we take a closer look at Official Statistics from a findable, accessibility, interoperability, and reusability (FAIR) perspective. Digital Objects in Statistics Digital objects in official statistics can be identified on multiple levels. The core concept is the statistical fact: a number describing a certain estimate on a certain phenomenon in a certain population over a certain period of time. For example the estimated number of elderly inhabitants in Province Friesland (the Netherlands) on Jan 1, 2020, or the inflation in Belgium for fruits in 2021 are both statistical facts. Each of these statistical facts is uniquely defined and published as a digital object in the online statistical databases of Statistics Netherlands and Eurostat respectively. Statistical facts may have a production status (provisionary, final, revised) and are typically visualized as a number in a table cell or in a chart. Data without metadata are without meaning. A statistical fact refers to metadata (region, time, subject, population, uncertainty, quality etc.) which are essential to understand the context of the fact. We make a distinction here between structural or conceptual metadata, i.e. the structure and definitions of concepts, dimensions and types of data used, and referential metadata, i.e. descriptive information on the dataset. The metadata are of utmost importance to the data consumer to understand the data. Metadata have their own dynamics, e.g. classifications change over time. They are published as digital objects too, for example the statistical classification of economic activities (NACE). Statistical facts and their metadata form the foundation for higher level statistics products. News releases and thematic articles that explain statistics in a broader context are examples. This higher level content can be seen as digital objects too as it is usually the main entry level for the general public and search engines and enables their findability and accessibility. Standards and FAIR Each digital object in official statistics has its own structure, dynamics, dissemination channels and standards. This can make it sometimes hard to work with data from official statistics. Statistical databases differ among statistical organizations, both technically as well as in metadata and the API’s that they offer for automated access. Main standards in this field are the Statistical Data and Metadata eXchange (SDMX), JSON-stat, OData, or simple formats such as CSV. Commonly agreed structural metadata is organized into SDMX registries (global registry, Eurostat registry), which provide automated access to statistical metadata, which is good for accessibility. The SDMX standard is actually targeted to statistical and financial data which may hinder wider reusability. Therefore some statistical offices are moving to semantic standards. An an example are the vocabularies and classifications published as linked open data by Statistics Netherlands. Publishing metadata this way makes it possible to reuse and link data across organizations and gives semantic structure that is machine readable. Another example is from the statistical office of the European Union, Eurostat, that is converting the statistical classifications and correspondence tables from their current metadata system into Linked Open Data in the EU Vocabularies website. The representation is based on XKOS, an ontology for modelling statistical classifications, offering machine-readable access for reusing objects as well as facilitating linking among classifications on national, EU or international level. Yet another initiative is from the United Nations Economic Commission for Europe (UNECE), where statistical organizations collectively develop a Core Ontology for Official Statistics (COOS) describing the statistical production process. All in all for structural metadata, statistical organizations are increasingly moving towards linked data standards to better align to non-statistical communities. In the field of referential metadata the Single Integrated Metadata Structure (SIMS) is used. It offers machine-readable descriptive metadata such as unit of measure, reference period, confidentiality, quality, accuracy etc. Some of the elements are also covered in the widely used RDF-based Data Catalog Vocabulary (DCAT) and the statistical variant (STAT-DCAT), which raises the question whether a further integration of these could improve FAIR-ness of statistical referential metadata. With respect to higher level digital objects, such as statistical articles, the use of semantic web ontologies such as schema.org and Dublin Core for annotating statistical output in common terms are increasingly being used. The use of Digital Object Identifiers (DOIs) where applicable makes it easier to refer to statistical output. From the above we can see that the use of different standards at different levels creates various ways to identify statistical content, such as Uniform Resource Names (URNs), SDMX identifiers, Digital Object Odentifiers (DOIs), Uniform Resource Identifiers (URIs) or organization specific identifiers. Although they probably all satisfy FAIR principle A1, from a user perspective it would be good to minimize variety here. Wrap-up Although official statistics have a long tradition and experience in publishing open data, the FAIR principles are an excellent vehicle to further improve findability and enable data-driven work. Openness is not enough, the facts, structural and referential metadata and higher level statistical digital objects should ideally all be optimized from a FAIR point of view. The mix of standards being used at various levels and the distributed statistical system in official statistics may hinder reusability. Moving to semantic-interoperability via generally accepted linked data standards is ongoing and has the promise to increase the reusability of statistics into a broader web of (meta)data. This makes trustful statistics more FAIR, better searchable, findable and interpretable which is necessary for a further integration of official statistics into wider communities.