Relevant bibliographies by topics / System Dynamics Model (SDM)

Academic literature on the topic 'System Dynamics Model (SDM)'

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Published: 14 March 2023

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Journal articles on the topic "System Dynamics Model (SDM)"

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Dang, Dongfang, Feng Gao, and Qiuxia Hu. "Motion Planning for Autonomous Vehicles Considering Longitudinal and Lateral Dynamics Coupling." Applied Sciences 10, no. 9 (May 2, 2020): 3180. http://dx.doi.org/10.3390/app10093180.

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Vehicles are highly coupled and multi-degree nonlinear systems. The establishment of an appropriate vehicle dynamical model is the basis of motion planning for autonomous vehicles. With the development of autonomous vehicles from L2 to L3 and beyond, the automatic driving system is required to make decisions and plans in a wide range of speeds and on bends with large curvature. In order to make precise and high-quality control maneuvers, it is important to account for the effects of dynamical coupling in these working conditions. In this paper, a new single-coupled dynamical model (SDM) is proposed to deal with the various dynamical coupling effects by identifying and simplifying the complicated one. An autonomous vehicle motion planning problem is then formulated using the nonlinear model predictive control theory (NMPC) with the SDM constraint (NMPC-SDM). We validated the NMPC-SDM with hardware-in-the-loop (HIL) experiments to evaluate improvements to control performance by comparing with the planners original design, using the kinematic and single-track models. The comparative results show the superiority of the proposed motion planning algorithm in improving the maneuverability and tracking performance.
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YU, Xiaohan, Zeshui XU, and Shousheng LIU. "SYSTEMATIC DECISION MAKING: A EXTENDED MULTI-CRITERIA DECISION MAKING MODEL." Technological and Economic Development of Economy 23, no. 1 (January 22, 2017): 157–77. http://dx.doi.org/10.3846/20294913.2016.1212121.

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Considering some complex multi-criteria decision making (MCDM) problems, in which decision environment is dynamic, there are various interdependences among criteria, and plans (systematized alternatives) consisting of multiple time sequential interdependent actions, cannot be well handled by means of the existing MCDM methods, therefore, we develop a systematic decision making (SDM) as an improvement and supplement of the classic MCDM in this paper. The SDM is for prescribing methods of evaluating and selecting the most favourite plan (a system) from a group of feasible ones concerning influences of time-varying criteria system under dynamic external environment. Through detailed analysis, we separate a SDM problem into multi-period MCDM subproblems, and then a plan can be a combination of time sequential strategies in which each strategy (a subset of actions) is a feasible decision choice of corresponding MCDM sub-problem. After clarifying variety of interdependences, interactions and interrelationships in the SDM problems, such as criteria-interdependences, action-interdependences, interactions between criteria and criteria system, interactions between actions and strategies, interactions between strategies and plans, interactions between internal environment (criteria system) and external environment, feedbacks from external environment to the corresponding MCDM sub-problems, and interrelationships among MCDM sub-problems and so on, we transform the SDM into multi-period interrelated MCDM model which can be dealt with more easily by using multiple optimization models. At the end of the paper, three typical properties of the SDM are proposed and most of the existing MCDM models are pointed out as special cases of the SDM.
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Litvinenko, V., and M. Dvoinikov. "Methodology for determining the parameters of drilling mode for directional straight sections of well using screw downhole motors." Journal of Mining Institute 241 (February 25, 2020): 105. http://dx.doi.org/10.31897/pmi.2020.1.105.

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Article presents results of study on possibility of increasing the efficiency of drilling directional straight sections of wells using screw downhole motors (SDM) with a combined method of drilling with rotation of drilling string (DS). Goal is to ensure steady-state operation of SDM with simultaneous rotation of DS by reducing the amplitude of oscillations with adjusting the parameters of drilling mode on the basis of mathematical modeling for SDM – DS system.Results of experimental study on determination of extrema distribution of lateral and axial oscillations of SDM frame depending on geometrical parameters of gerotor mechanism and modes ensuring stable operation are presented.Approaches to development of a mathematical model and methodology are conceptually outlined that allow determining the range of self-oscillations for SDM – DS system and boundaries of rotational and translational wave perturbations for a heterogeneous rod with an installed SDM at drilling directional straight sections of well. This mathematical model of SDM – DS system's dynamics makes it possible to predict optimal parameters of directional drilling mode that ensure stable operation of borehole assembly.
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SERAJI, Salameh, Hasan MEHRMANESH, and Ahmad R. KASRAEE. "Design of a System Dynamics Model (SDM) to Evaluate the Supply Chain of Biological Products." International Journal of Engineering Technologies IJET 7, no. 2 (June 24, 2021): 20–32. http://dx.doi.org/10.19072/ijet.827233.

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Bottero, Marta, Giulia Datola, and Elena De Angelis. "A System Dynamics Model and Analytic Network Process: An Integrated Approach to Investigate Urban Resilience." Land 9, no. 8 (July 23, 2020): 242. http://dx.doi.org/10.3390/land9080242.

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During the last decade, the concept of urban resilience has been increasingly implemented in urban planning, with the main aim to design urban development strategies. Urban resilience is a multi-dimensional and dynamic concept. When applied to urban planning, it consists of studying cities as complex socio-economic systems. Municipalities are currently working to undertake appropriate actions to enrich the resilience of cities. Moreover, several difficulties concern the evaluation of the impacts over time of the strategies designed to enhance urban resilience. The present paper proposes an integrated approach based on the System Dynamics Model (SDM) and the Analytic Network Process (ANP). The objective of this research is to describe the method and to illustrate its application to the area called Basse di Stura, located in the city of Turin, Italy. The method is applied to evaluate the possible impacts of two different urban scenarios in terms of the change of urban resilience performance over time. The final result is represented by an index that describes urban resilience performance.
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Momodu, Abiodun S., and Lucy Kivuti-Bitok. "System dynamic modelling of electricity planning and climate change in West Africa." AAS Open Research 1 (May 2, 2018): 15. http://dx.doi.org/10.12688/aasopenres.12852.1.

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Background: It is imperative to develop an efficient strategic approach to managing the push-pull factor in economic development, particularly as relates to climate change and energy interactions in the West African Region. This article demonstrates the use of System Dynamics Modelling (SDM) for that purpose; to manage the development of energy growth with reduced impact in regards to climate change. The complexities of energy planning in relation to climate change necessitates the need for the tool to examine low carbon economy mixed with traditional approaches of planning. Methods: Vensim DSS version 6.2 was used to develop the model. WAPP member country level data elicited from WAPP and ECOWAS Regional Electricity Regulatory Authority (ERERA) serves as the set of basic data used to develop and run the main model. These were complemented with other data elicited from various journal articles and internet sources. These include population and its average growth rate, GDP, per capita income, average per capita electricity demand, electricity generated, average electricity tariff, generation technology type, amongst others. Results: SDM demonstrates the capability to understand the theoretical frame for trade-offs between economic development and climate change, by handling the nonlinear relationship between generation adequacy and greenhouse gas (GHG) emission reduction for better targeted strategic regional intervention on climate change. Conclusion: The primary goal of this paper was to demonstrate the use of SDM to aid in resource planning in an inexpensive way to examine low carbon pathway. With the SDM, the goal of low carbon pathway in the energy system was achieved without the cost of controlled trials.
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Momodu, Abiodun S., and Lucy Kivuti-Bitok. "System dynamic modelling of electricity planning and climate change in West Africa." AAS Open Research 1 (October 4, 2018): 15. http://dx.doi.org/10.12688/aasopenres.12852.2.

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Background: It is imperative to develop an efficient strategic approach to managing the push-pull factor in economic development, particularly as relates to climate change and energy interactions in the West African Region. This article demonstrates the use of System Dynamics Modelling (SDM) for that purpose; to manage the development of energy growth with reduced impact in regards to climate change. The complexities of energy planning in relation to climate change necessitates the need for the tool to examine low carbon economy mixed with traditional approaches of planning. Methods: Vensim DSS version 6.2 was used to develop the model. WAPP member country level data elicited from WAPP and ECOWAS Regional Electricity Regulatory Authority (ERERA) serves as the set of basic data used to develop and run the main model. These were complemented with other data elicited from various journal articles and internet sources. These include population and its average growth rate, GDP, per capita income, average per capita electricity demand, electricity generated, average electricity tariff, generation technology type, amongst others. Results: SDM demonstrates the capability to understand the theoretical frame for trade-offs between economic development and climate change, by handling the nonlinear relationship between generation adequacy and greenhouse gas (GHG) emission reduction for better targeted strategic regional intervention on climate change. Conclusion: The primary goal of this paper was to demonstrate the use of SDM to aid in resource planning in an inexpensive way to examine low carbon pathway. With the SDM, the goal of low carbon pathway in the energy system was achieved without the cost of controlled trials.
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Tuu, Nguyen Thanh, Jeejae Lim, Seungdo Kim, Van Pham Dang Tri, Hyeonkyeong Kim, and Jeonghoon Kim. "Surface water resource assessment of paddy rice production under climate change in the Vietnamese Mekong Delta: a system dynamics modeling approach." Journal of Water and Climate Change 11, no. 2 (January 2, 2019): 514–28. http://dx.doi.org/10.2166/wcc.2019.176.

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Abstract Water demands and stresses in the Vietnam Mekong Delta (VMD) are of high concern for the coming decade. System dynamics modeling (SDM) can be used to understand the impacts of the changes on water resources at a regional scale. SDM framework was applied to assess the impacts of land use changes and climate on surface water resource in the VMD. The developed model was modified from a global-scale model and added in-situ specific variables to model the conditions of the VMD using historical data during 1986–2005, and future projections to 2050 under two Representative Concentration Pathways scenarios (RCP4.5 and RCP8.5). Projected changes in land use and population were based on the most recent governmental resolution to support adaptation and the national plans. Temperature and rainfall changes cause the increase in water stress; however, it could be mitigated by shifting from three to two crops of rice each year. Water stress differs from place to place, such as in freshwater and brackish coastal zones. Water stress is most strongly affected by changed temperature, rather than rainfall. The developed system dynamics model and framework can be effectively applied in the VMD to support decision-making about sustainable water use for paddy rice.
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Farhan, Muhammad, Hassan Mobeen Alam, and Shaista Jabeen. "Managing Equity Investment Risk and Rate of Return Risk in Islamic Banking: A System Thinking Approach." Business & Economic Review 13, no. 1 (March 15, 2021): 43–64. http://dx.doi.org/10.22547/ber/13.1.3.

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This study aims to examine and explore the risk management practices with respect to Rate of Return Risk (RORR) and Equity Investment Risk (EIR) in the Islamic Banking Institutions (IBIs) of Pakistan through a systematic model which is called System Dynamic Model (SDM) by using system thinking methodology. This study has been conducted in three sequential phases to develop the qualitative System Dynamic Model for Rate of Return Risk Management and Equity Investment Risk Management. Firstly, the researchers developed preliminary Causal Loop Diagrams (CLD) based on the initial understanding achieved from the causal interconnections between various RORR and EIR characters through extensive literature review. Secondly, the researchers conducted semi-structured interviews with the experts to ratify, endorse and refine the initial CLD. Lastly, the data collected through interviews was analyzed to develop the final refined qualitative SDM. The study's findings indicate that the identification and measurement of the RORR and EIR in IBIs in Pakistan need to be strengthened by developing appropriate methodology. Moreover, the practices adopted by these financial institutions to mitigate and control the exposures of RORR and EIR are good and effective. This Qualitative SDM provides practical, constructive and productive understanding to the managers, policy-makers, regulators, shareholders and scholars regarding the RORR and EIR management mechanism of IBIs of Pakistan.
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Coyle, R. G. "A system dynamics model of aircraft carrier survivability." System Dynamics Review 8, no. 3 (1992): 193–212. http://dx.doi.org/10.1002/sdr.4260080302.

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Dissertations / Theses on the topic "System Dynamics Model (SDM)"

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Egbunike, Chukwudi Muofunanya Uchenna. "A system dynamics mineral exploitation model." Thesis, Imperial College London, 1987. http://hdl.handle.net/10044/1/38295.

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Liu, Fuping. "A system dynamics model for hydropower generation planning." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2002. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/MQ62782.pdf.

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Jootar, Jay 1975. "A risk dynamics model of complex system development." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/8480.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Sloan School of Management, 2002.
Includes bibliographical references (p. 201-204).
The development of complex systems is a challenging endeavor which has captured the attentions of scholars and practitioners alike. Throughout the decades, numerous methods have been proposed to help manage such development efforts more effectively and efficiently. Some of these methods, such as prototyping, concurrent engineering, iterative model for software development, and system-focused development for R&D, are process models which recommend better ways to structure the development process to handle the complexity of the system under development. This thesis seeks to understand the complex system development from a risk perspective. Continuing from the work done by other researchers, this work combines issues which are traditionally considered separately into one single model. More specifically, the model explicitly captures the dependencies in the system and the structure of an iterative development process and their interactions. The resulting mathematical problem demonstrates the risk characteristics of a development process. It shows that the optimality calls for a trade-off between the reduction of the probability of risk and the increase in the impact of risk. From its structure, the model also helps us understand how different aspects of system architecture affect the structure and the performance of the development process. In addition, the model also reveals the fundamental problems of process models and proposes a generic risk-based alternative. To explore the applicability of the model, the thesis also provides a case study in a software development process and a set of heuristics for solving the resulting combinatorial problem.
by Jay Jootar.
Ph.D.
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Tan, HockWoo. "Agent-based model and system dynamics model for peace-keeping operations." Thesis, Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/44010.

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Approved for public release; distribution is unlimited
Military operations other than war (MOOTW) make up a large percentage of total military operations. Some common MOOTW operations are peacekeeping (PKO) and humanitarian assistance, and disaster relief (HADR). System dynamics (SD) uses a top-down approach that models high-level system behavior as compared to the use of agent-based modeling (ABM), which uses a bottom-up approach to generate system-level behavior through emergent behavior. In this work, SD and ABM were applied to model a food distribution scenario during the early phases of PK/HADR and the implementation process and results compared. The results were that large variations in food prices were observed as the time step and the integration technique were varied. Both SD and ABM, however, displayed similar emergent behavior in terms of crimes that occurred due to relative deprivation within the population. As an alternative to time step approximation, discrete event simulation (DES) may be used to implement the SD model through discretization of stocks or flows within the system and identifying events that change these quantities. The quantization of continuous variables in SD into discrete quantities may, however, introduce quantization errors. Emergent behavior seen in ABM can occur in SD through the interactions between equations. Due to the compactness of SD equations, it feels less intuitive to develop models using SD than it does to develop models using ABM.
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Sontamino, Phongpat. "Decision support system of coal mine planning using system dynamics model." Doctoral thesis, Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2015. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-159919.

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Coal is a fossil fuel mineral, which is presently a major source of electricity and energy to industries. From past to present, there are many coal reserves around the world and large scale coal mining operates in various areas such as the USA, Russia, China, Australia, India, and Germany, etc. Thailand’s coal resources can be found in many areas; there are lignite mining in the north of Thailand, the currently operational Mae Moh Lignite Mine, and also coal reserves in the south of Thailand, such as Krabi and Songkhla, where mines are not yet operating. The main consumption of coal is in electricity production, which increases annually. In 2019, the Thai Government and Electricity Generating Authority of Thailand (EGAT) plans to run a 800 MW coal power plant at Krabi, which may run on imported coal, despite there being reserves of lignite at Krabi; the use of domestic coal is a last option because of social and environmental concerns about the effects of coal mining. There is a modern trend in mining projects, the responsibility of mining should cover not only the mining activity, but the social and environmental protection and mine closure activities which follow. Thus, the costs and decisions taken on by the mining company are increasingly complicated. To reach a decision on investment in a mining project is not easy; it is a complex process in which all variables are connected. Particularly, the responsibility of coal mining companies to society and the environment is a new topic. Thus, a tool to help to recognize and generate information for decision making is in demand and very important. In this thesis, the system dynamics model of coal mine planning is made by using Vensim Software and specifically designed to encompass many variables during the period of mining activity until the mine closure period. The decisions use economic criteria such as Net Present Value (NPV), Net Cash Flow (NCF), Payback Period (PP), and Internal Rate of Return (IRR), etc. Consequently, the development of the decision support system of coal mine planning as a tool is proposed. The model structure covers the coal mining area from mine reserves to mine closure. It is a fast and flexible tool to perform sensitivity analysis, and to determine an optimum solution. The model results are clear and easily understandable on whether to accept or reject the coal mine project, which helps coal mining companies make the right decisions on their policies, economics, and the planning of new coal mining projects. Furthermore, the model is used to analyse the case study of the Krabi coal-fired power plant in Thailand, which may possibly use the domestic lignite at Krabi. The scenario simulations clearly show some potential for the use of the domestic lignite. However, the detailed analysis of the Krabi Lignite Mine Project case shows the high possible risks of this project, and that this project is currently not feasible. Thus, the model helps to understand and confirm that the use of domestic lignite in Krabi for the Krabi Coal Power Plant Project is not suitable at this time. Therefore, the best choice is imported coal from other countries for supporting the Krabi Coal Power Plant Project. Finally, this tool successfully is a portable application software, which does not need to be installed on a computer, but can run directly in a folder of the existing application. Furthermore, it supports all versions of Windows OS.
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Mbiti, Titus Kivaa Peter, and tkivaap@yahoo com. "A System Dynamics Model of Construction Output in Kenya." RMIT University. Property Construction & Project Management, 2008. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20081211.160910.

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This study investigates fluctuations of construction output, and growth of the output in Kenya. Fluctuation and growth of construction activity are matters of concern in construction industries of many countries in the developing as well as in the developed world. The construction industry of Kenya is therefore an exemplifying case for this phenomenon. Construction activity in Kenya fluctuates excessively and grows very slowly. This remains a big challenge to policy makers, developers, consultants and contractors in their decision-making processes. In this study, systems thinking was applied to investigate the problem of excessive fluctuations and stunted growth of construction output in Kenya. The study developed a system dynamics model to simulate the construction output problem behaviour. The historical behaviour of the construction industry was described using construction output data of a 40-year period - from 1964 to 2003. Line graphs of the historical data exhibited profiles that helped to identify the system archetypes operating in the industry. From the profiles, it was deduced that the problem of fluctuations and slow growth of construction output in Kenya is encapsulated in two system archetypes, namely: balancing process with a delay, and limits to growth. The relationship between construction output and its determinant factors from the constru ction industry's environment was investigated using time series regression, which involved autoregressive integrated moving average (ARIMA) regression and multiple regression modelling of the output. On the basis of the historical data analysis and the system archetypes identified, a system dynamics (SD) model was developed to replicate the problem of fluctuations and slow growth in the construction output. The data used to develop the system dynamics model was annual construction output in Kenya from 1964 to 2003. The model was then used: to appraise policy changes suggested by construction industry participants in Kenya, and to project construction output in Kenya from year 2004 to year 2050, in order to establish the expected future fluctuations and growth trends of the construction output. It was observed that three fundamental changes are necessary in the system structure of the construction industry of Kenya, in order to minimize fluctuations and foster growth in construction output in the country, in the long run. The changes are: setting long-term targets of annual construction output in the industry as a whole, incorporating reserve capacity in the production process, and expanding the system st ructure to capture a larger construction market. The study recommends regulation of the response of the construction industry of Kenya to changes in construction demand in the market, and expansion of the construction industry's market into the African region and beyond.
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Yung, Christian Hung Shing. "The privatization process--a system dynamics model for Brazil." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/12086.

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Gozluklu, Burak. "A new project management system dynamics model and simulator." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113517.

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Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 56-57).
Simulators generated from project management system dynamics models are exercised for training the future project managers. In today's' high dynamic, vibrant and complex markets, the models should incorporate more business dynamics and also provide more tools to the players who can flexibly steer in the project games. Along with that objective, this study brings new dynamics and modeling approach to the original multi-phase project system dynamics model of Ford and Sterman, 1998. The new dynamics include the development of new features in the market growing the customer expectation, reflection of customer expectation to project economics, supersede of project concurrencies by rushing the tasks, allowing the defects delivered to customers to be compensated by lifetime repair cost and free positioning of the phase schedules while maintaining concurrencies. A new formulation for completion putthrough, option to include final downstream defect correction and elaborate project econometrics are also included. The model is built in modules that can be utilized to increase the number of phases and/or explain the model to the trainees more easily. The project model employs two options; a zero-defect policy and allowed defect policy where the latter is newly introduced by the repair cost. The system dynamics model is tested by proposed extreme project manager traits which are implemented as table function to use one or more modules to pursue an ultimate objective within a certain logic. A construction project principally mimicking the cases provided by Parvan et al. 2015 is simulated with the manager traits. The results initiate interesting tradeoffs such as the influence of project delivery time versus repair cost, accepting new tasks versus creating more defects or rescheduling the project or positioning the workforce before the ramping up of testing and defective task correction activities. The model necessitates a deeper understanding and analyses of long-term phenomenon such as the lifetime repair cost, the financial consequences of defects and lifetime earnings of products as well as the continuous feature development in the market and its economic value. It is found that the current model proposes an enhanced tool for the training of future project managers. Keywords: System dynamics, project management, simulation, defect policy, numerical modeling.
by Burak Gozluklu.
S.M. in Engineering and Management
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Quan, Chuanwen. "A system dynamics model for the development of China's air transportation system." Thesis, This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-09182008-063445/.

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Grobbelaar, Sara Susanna. "R&D in the national system of innovation a system dynamics model /." Pretoria : [s.n.], 2006. http://upetd.up.ac.za/thesis/available/etd-07212007-130132.

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Books on the topic "System Dynamics Model (SDM)"

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Awcock, M. J. A system dynamics model for communications networks. [Malvern, Worcs.]: Royal Signals & Radar Establishment, 1985.

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Group model building: Facilitating team learning using system dynamics. Chichester: J. Wiley, 1996.

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Sitompul, Rislima F. Merancang model pengembangan masyarakat pedesaan dengan pendekatan system dynamics. Jakarta: Lembaga Ilmu Pengetahuan Indonesia, 2009.

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Jones, G. N. Identification of system dynamics of a high incidence research model. Sheffield: University of Sheffield, Dept. of Control Engineering, 1990.

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David, Hampton Roy, and George C. Marshall Space Flight Center., eds. A " Kane's Dynamics" model for the active rack isolation system. Marshall Space Flight Center, Ala: National Aeronautics and Space Administration, Marshall Space Flight Center, 2001.

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Rocşoreanu, C. The FitzHugh-Nagumo model: Bifurcation and dynamics. Dordrecht: Kluwer Academic Publishers, 2000.

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Grancharova, Alexandra. Explicit Nonlinear Model Predictive Control: Theory and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Antonio, Palacios, Schweitzer Frank, Kacprzyk Janusz, Sornette Didier 1957-, Érdi Péter, Schuster Peter, Reichl L. E, et al., eds. Applications of Nonlinear Dynamics: Model and Design of Complex Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009.

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A, Mulac Richard, Celestina Mark L, and Lewis Research Center, eds. A model for closing the inviscid form of the average-passage equation system. [Cleveland, Ohio: National Aeronautics and Space Administration, Lewis Research Center, 1986.

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Merten, Peter P. Know-how transfer by multinational corporations to developing countries: A system dynamics model with spiral loops. Cambridge, Mass: Sloan School of Management, Massachusetts Institute of Technology, 1986.

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Book chapters on the topic "System Dynamics Model (SDM)"

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Koch, Manuel, and Karl Pauls. "An Access Control Language for Dynamic Systems – Model-Driven Development and Verification." In SDL 2005: Model Driven, 16–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11506843_2.

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Rouwette, Etiënne A. J. A., and Jac A. M. Vennix. "Group Model Building." In System Dynamics, 91–107. New York, NY: Springer US, 2020. http://dx.doi.org/10.1007/978-1-4939-8790-0_264.

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Olaya, Camilo. "System Dynamics: Engineering Roots of Model Validation." In System Dynamics, 109–17. New York, NY: Springer US, 2020. http://dx.doi.org/10.1007/978-1-4939-8790-0_544.

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Scott, Rodney J., Robert Y. Cavana, and Donald Cameron. "Interpersonal Success Factors for Strategy Implementation: A Case Study Using Group Model Building." In System Dynamics, 133–62. London: Palgrave Macmillan UK, 2017. http://dx.doi.org/10.1057/978-1-349-95257-1_5.

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Findeisen, Dietmar. "System Representation by Diagrams (Model System)." In System Dynamics and Mechanical Vibrations, 9–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-662-04205-2_2.

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Pasquinelli, Mauro, Luis Molina-Tanco, Arcadio Reyes-Lecuona, and Michele Cencetti. "Extending the System Model." In Dynamics of Long-Life Assets, 169–89. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-45438-2_10.

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Shu, Zhong, Boer Deng, Luo Tian, Fen Duan, Xinyu Sun, Liangzhe Chen, and Yue Luo. "Construction of SDN Network Management Model Based on Virtual Technology Application." In Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications, 257–68. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2456-9_28.

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AbstractThis paper designs a virtual SDN network management model constrained by fair and equal network management information access mechanisms by analyzing the problems existing in the universality of existing SDN network management models. Starting with the three-tier structure of the SDN network management system, the main parameters involved in the network management service function, information processing and transmission channel construction in the system were strictly and normatively defined. The design of virtual nodes is regarded as the core element of the network management system, and the information transmission inside it adopts logical operation; The network management service function and the channel for realizing the network management service function are isolated, and the iterative search, analysis and update mechanism is enabled in the network management information transmission channel. By constructing the experimental verification platform and setting the evaluation parameters of the system performance objectives, the scalability and timeliness of the model were evaluated from two aspects: the deployment of network virtual nodes and the dynamic control of network management information channels. The collected experimental core evaluation parameters, the realization time of the network management service function, can show that the dynamic distribution mechanism of network management information can be cross-applied to each virtual node, and the channel update mechanism of network management information can adjust the information processing queue in real-time. The network management system model that has been built realizes the separation of management and control of the network management system and has the characteristics of independent operation, autonomous function, self-matching, rapid deployment and dynamic expansion.
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van der Schaft, Arjan, and Bernhard Maschke. "Conservation Laws and Lumped System Dynamics." In Model-Based Control:, 31–48. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0895-7_3.

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Hovmand, Peter S. "Group Model Building Workshop and Facilitation." In Community Based System Dynamics, 61–76. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8763-0_6.

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Hovmand, Peter S. "Model Refinement, Integration, Formulation, and Analysis." In Community Based System Dynamics, 77–90. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8763-0_7.

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Conference papers on the topic "System Dynamics Model (SDM)"

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Martin, Guillaume, Etienne Balmes, Thierry Chancelier, Sylvain Thouviot, and Rémi Lemarie. "A Structural Dynamics Modification Strategy based on Expanded Squeal Operational Deflection Shapes." In EuroBrake 2022. FISITA, 2022. http://dx.doi.org/10.46720/eb2022-tsd-009.

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"To analyse brake squeal, measurements are performed to extract the Operational Deflection Shape (ODS) characteristic of the limit cycle. The advantage of this strategy is that the real system behaviour is captured, but measurements suffer from a low spatial distribution and hidden surfaces, so that interpretation is sometimes difficult. It is even more difficult to propose system modifications from test alone. Historical Structural Dynamics Modification (SDM) techniques need mass normalized shapes which is not available from an ODS measurement. Furthermore, it is very difficult to translate mass, damping or stiffness modification between sensors into physical modifications of the real system. On the model side, FEM methodology gives access to fine geometric details, continuous field over the whole system. Simple simulation of the impact of modifications is possible, one typical strategy for squeal being to avoid unstable poles. Nevertheless, to ensure accurate predictions, test/FEM correlation must be checked and model updating may be necessary despite high cost and absence of guarantee on results. To combine both strategies, expansion techniques seek to estimate the ODS on all FEM DOF using a multi-objective optimization combining test and model errors. The high number of sensors compensates for modelling errors and while allowing imperfect test. The Minimum Dynamics Residual Expansion method used here, ensures that the complex ODS expanded shapes are close enough to the measured motion but have smooth, physically representative, stress field, which is mandatory for further analysis. From the ODS expansion, the two underlying real shapes are mass-orthonormalized and stiffness-orthogonalized using the model resulting in a reduced model with two modes known on the full model. Sensitivity analysis is thus possible and the impact of thickness modifications on frequencies is built. This provides a novel structural modification strategy where the parameters are thickness distributions, and the objective is to separate the frequencies associated with the two shapes found by expansion of the experimental ODS. The methodology will be illustrated for a recent disk brake test and model. "
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Shvetsov, E. G., N. M. Tchebakova, and E. I. Parfenova. "Using remote sensing data in population density estimation." In Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021. Crossref, 2021. http://dx.doi.org/10.25743/sdm.2021.34.56.066.

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In recent decades, remote sensing methods have often been used to estimate population density, especially using data on nighttime illumination. Information about the spatial distribution of the population is important for understanding the dynamics of cities and analyzing various socio-economic, environmental and political factors. In this work, we have formed layers of the nighttime light index, surface temperature and vegetation index according to the SNPP/VIIRS satellite system for the territory of the central and southern regions of the Krasnoyarsk krai. Using these data, we have calculated VTLPI (vegetation temperature light population index) for the year 2013. The obtained values of the VTLPI calculated for a number of settlements of the Krasnoyarsk krai were compared with the results of the population census conducted in 2010. In total, we used census data for 40 settlements. Analysis of the data showed that the relationship between the value of the VTLPI index and the population density in the Krasnoyarsk krai can be adequately fitted (R 2 = 0.65) using a linear function. In this case, the value of the root-meansquare error was 345, and the relative error was 0.09. Using the obtained model equation and the spatial distribution of the VTLPI index using GIS tools, the distribution of the population over the study area was estimated with a spatial resolution of 500 meters. According to the obtained model and the VTLPI index, the average urban population density in the study area exceeded 500 people/km2 . Comparison of the obtained data on the total population in the study area showed that the estimate based on the VTLPI index is about 21% higher than the actual census data.
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Kirsta, Yu B., A. V. Puzanov, T. A. Rozhdestvenskaya, and M. P. Peleneva. "Long-term forecast of heavy metals content in wheat grain under changing climate conditions." In Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021. Crossref, 2021. http://dx.doi.org/10.25743/sdm.2021.58.67.055.

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Using the system approach, we have developed a simulation model for the long-term forecast of the content of toxic chemical elements in grain crop yield. The study was carried out by the example of wheat cultivated in Altai Krai — one of the main grain-producing regions of Russia. Wheat crops were sampled in 10 municipal districts of Altai Krai, which characterize seven different edaphic-climatic zones. The average long-term values of mean monthly air temperature and monthly precipitation for each sampling area were identified using GIS and data of the Interactive Agricultural Ecological Atlas of Russia and Neighboring Countries. A total of 19 chemical elements were considered, i.e. Pb, As, Cd, Hg, Na, Mn, Zn, Cu, Fe, Co, etc. It is shown that content of Pb, Na, Mn and Cu in wheat depend on climatic characteristics of the cultivation area. Regression dependences of element content on the average long-term air temperature and precipitation were established. Based on normalization and spatial generalization of air temperature and precipitation providing the uniform dynamics of their relative monthly values (in percent) throughout the study area, a forecast of their changes was made for 2030. A procedure for grain sampling, GIS technologies for processing meteorological and cartographic data, methods for predicting regional climate changes and establishment of quantitative relationships of chemical elements content in grain with climatic characteristics – all together make up the integral predictive simulation model for toxic substance content in grain crop yield. The model was used for estimation of Pb, Na, Mn, Cu changes in wheat by 2030. The lead (Pb) content in wheat crop delivered to elevators from certain municipal districts will exceed the maximum allowable concentration for breadgrain after 2030. Unlike Pb, Na, Mn, Cu, the content of other metals in wheat grain weakly correlate with long-term changes in air temperature and precipitation; therefore, it can hardly change significantly.
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Lin, Chan-Chiao, Huei Peng, Min Joong Kim, and Jessy W. Grizzle. "Integrated Dynamic Simulation Model With Supervisory Control Strategy for a PEM Fuel Cell Hybrid Vehicle." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-61775.

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System-level modeling and control strategy development for a hybrid fuel cell vehicle (HFCV) are presented in this paper. A reduced-order fuel cell model is created to accurately predict the fuel cell system efficiency while retaining dynamic effects of important reactant variables. The fuel cell system model is then integrated with a DC/DC converter, a Li-Ion battery, an electric drive and tire/vehicle dynamics to form a HFCV. The supervisory-level control problem of the HFCV is subsequently investigated. A stochastic dynamic programming (SDP) based approach is applied to obtain an optimal power management strategy. Simulations over different driving cycles showed that the SDP control strategy not only saved a significant amount of hydrogen but also produced smoother load for the fuel cell stack—both of which help the long term viability of the fuel cell technology for automotive applications.
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Sadasivuni, Suresh Kumar, Ghenadie Bulat, Victoria Sanderson, and Nedunchezhian Swaminathan. "Application of Scalar Dissipation Rate Model to Siemens DLE Combustors." In ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/gt2012-68483.

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The standard design process for the Siemens Industrial Turbomachinery, Lincoln, Dry Low Emissions combustion systems has adopted the Eddy Dissipation Model with Finite Rate Chemistry for reacting computational fluid dynamics simulations. The major drawbacks of this model have been the over-prediction of temperature and lack of species data limiting the applicability of the model. A novel combustion model referred to as the Scalar Dissipation Rate Model has been developed recently based on a flamelet type assumption. Previous attempts to adopt the flamelet philosophy with alternative closure models have failed, with the prediction of unphysical phenomenon. The Scalar Dissipation Rate Model (SDRM) was developed from a physical understanding of scalar dissipation rate, signifying the rate of mixing of hot and cold fluids at scales relevant to sustain combustion, in flames and was validated using direct numerical simulations data and experimental measurements. This paper reports on the first industrial application of the SDRM to SITL DLE combustion system. Previous applications have considered ideally premixed laboratory scale flames. The industrial application differs significantly in the complexity of the geometry, unmixedness and operating pressures. The model was implemented into ANSYS-CFX using their inbuilt command language. Simulations were run transiently using Scale Adaptive Simulation turbulence model, which switches between Large Eddy Simulation and Unsteady Reynolds Averaged Navier Stokes using a blending function. The model was validated in a research SITL DLE combustion system prior to being applied to the actual industrial geometry at real operating conditions. This system consists of the SGT-100 burner with a glass square-sectioned combustor allowing for detailed diagnostics. This paper shows the successful validation of the SDRM against time averaged temperature and velocity within measurement errors. The successful validation allowed application of the SDRM to the SGT-100 twin shaft at the relevant full load conditions. Limited validation data was available due to the complexity of measurement in the real geometry. Comparison of surface temperatures and combustor exit temperature profiles showed an improvement compared to EDM/FRC model. Furthermore, no unphysical phenomena were predicted. This paper presents the successful application of the SDRM to the industrial combustion system. The model shows a marked improvement in the prediction of temperature over the EDM/FRC model previously used. This is of significant importance in the future applications of combustion CFD for understanding of hardware mechanical integrity, combustion emissions and dynamics of the flame.
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Leung, Chin-wing, Shuyue Hu, and Ho-fung Leung. "Modelling the Dynamics of Multi-Agent Q-learning: The Stochastic Effects of Local Interaction and Incomplete Information." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/55.

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The theoretical underpinnings of multiagent reinforcement learning has recently attracted much attention. In this work, we focus on the generalized social learning (GSL) protocol --- an agent interaction protocol that is widely adopted in the literature, and aim to develop an accurate theoretical model for the Q-learning dynamics under this protocol. Noting that previous models fail to characterize the effects of local interactions and incomplete information that arise from GSL, we model the Q-values dynamics of each individual agent as a system of stochastic differential equations (SDE). Based on the SDE, we express the time evolution of the probability density function of Q-values in the population with a Fokker-Planck equation. We validate the correctness of our model through extensive comparisons with agent-based simulation results across different types of symmetric games. In addition, we show that as the interactions between agents are more limited and information is less complete, the population can converge to a outcome that is qualitatively different than that with global interactions and complete information.
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Anusonti-Inthra, Phuriwat, and Subhadeep Chakraborty. "On the Use of CFD and Symbolic Dynamic Filtering for Health Monitoring of Rotating Machinery." In ASME 2014 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/dscc2014-6037.

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This paper presents an approach to use Computational Fluid Dynamics (CFD) analysis for the development of a health monitoring system based on Symbolic Dynamic Filtering (SDF) for rotating machinery. A simplified model of a turbomachinery (single rotor) is analyzed using commercial CFD software with and without blade damages. Virtual pressure sensors are placed on the case of the turbomachinery directly above the rotating blades to measure the dynamic pressure pulse generated by the rotating blades. The pressure pulse profiles from the rotating rotor blades with and without blade damages are processed using SDF to determine the presence and magnitude of the fault. Various degrees of damage and effect of measurement noise are examined.
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Schaefer, Frank R., Marc Ramsey, Imtiaz Haque, and Jürgen Schuller. "Development of Target Point Search Methods for Course Following Systems: Treating Vehicle Control." In ASME 2000 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/imece2000-1206.

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Abstract This paper addresses target point search methods for course following systems. A central concept in the development of the control algorithms for such systems is that of target point selection. For a given driving situation, target points constitute spatial objectives that the control algorithm strives to realize. The results presented in this paper are based on experiments made with a recently developed new driver model [Schaefer and Schuller, 1999]. The model establishes control in two steps: geometric dynamic planning and plan-to-action mapping. The separation into these two units allows one to investigate the process of target point search independently. Target point search is conducted for the guidance of a vehicle’s c.g., i.e. a system thats trajectory can be assumed to have ‘differentiable’ curvature profile. The concepts introduced here, however, may easily be generalized to any system whose state transition (i.e. trajectory) may be described locally by instantaneous circles and that has to follow an abstract nominal path in the state space. A so called situational driving motivation ‘SDM’ is formulated that defines a clear guideline for geometric dynamic planning based on an time isolated situation. A number of different search methods including Preview Point Search, End of Sight Search, Deviation Dependent Preview Point, and a so-called Nestle Point Search, are investigated. The results are evaluated on the basis of the vehicle’s ability to go around a course with a minimum lateral deviation from the nominal course. The results show that the Nestle Curve Search method provides the best performance.
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Alyaser, Monem, Rajesh Nair, and Prabhu Sathyamurthy. "CFD Modeling of Indirectly Fired Integrated Oxygen-Free Gasification and Steam Generation System." In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-40942.

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This paper introduces a novel gasification reactor that uses a process of steam gasification of the carbonaceous feedstock by indirectly heating the reacting flow through a high temperature heat exchanger without the need for partial with pure oxygen. It demonstrates the importance of gasification as a method for increasing power plant efficiency and reducing emissions. A computational fluid dynamics (CFD) model was created to model this novel gasifier and the results of the model that illustrates the efficiency and advantages of the new gasifier. The heating fuel was assumed to be fully combusted at the inlet. The adiabatic flame temperature was assumed to be the inlet temperature of the heating gas. The gasification stream was modeled as a laminar flow, where the reaction is kinetically controlled. The standard Shrinking Core Model (SCM) included in the commercial CFD package Fluent was used to predict the char consumption. The coal conversion rates were found to be higher than expected. The results indicate that the gasification of coal with steam without partial combustion with pure oxygen using this new concept is feasible.
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Kostyuchenko, Evgeny, Dariya Ignatieva, Roman Mescheryakov, Alexander Pyatkov, Evgeny Choynzonov, and Lidiya Balatskaya. "Model of system quality assessment pronouncing phonemes." In 2016 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2016. http://dx.doi.org/10.1109/dynamics.2016.7819016.

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Reports on the topic "System Dynamics Model (SDM)"

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Lyke, James C., and Josette Calixte-Rosengren. System Data Model (SDM) Source Code. Fort Belvoir, VA: Defense Technical Information Center, August 2012. http://dx.doi.org/10.21236/ada570990.

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Red-Horse, J. R. Structural system identification: Structural dynamics model validation. Office of Scientific and Technical Information (OSTI), April 1997. http://dx.doi.org/10.2172/469145.

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Maltrud, Mathew, and Phillip Wolfram. Marine Biogeochemical Dynamics in Coastally Refined Earth System Model Simulations. Office of Scientific and Technical Information (OSTI), April 2021. http://dx.doi.org/10.2172/1779652.

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Myers, Rodney S., Michael E. McDevitt, and Michael W. Zabarouskas. Surface Warfare Officer Community Management Model System Dynamics Proof-of-Concept. Fort Belvoir, VA: Defense Technical Information Center, February 2004. http://dx.doi.org/10.21236/ada421072.

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Malczynski, Leonard A. Best practices for system dynamics model design and construction with powersim studio. Office of Scientific and Technical Information (OSTI), June 2011. http://dx.doi.org/10.2172/1029812.

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Earl D Mattson and Larry Hull. Documentation of INL?s In Situ Oil Shale Retorting Water Usage System Dynamics Model. Office of Scientific and Technical Information (OSTI), December 2012. http://dx.doi.org/10.2172/1070124.

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Novak, William E., Andrew P. Moore, and Christopher Alberts. The Evolution of a Science Project: A Preliminary System Dynamics Model of a Recurring Software-Reliant Acquisition Behavior. Fort Belvoir, VA: Defense Technical Information Center, July 2012. http://dx.doi.org/10.21236/ada609942.

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Rice, Betsy M., Cary F. Chabalowski, George F. Adams, Richard C. Mowrey, and Michael J. Page. A Comparative Study of the Reaction Dynamics of a Model System Using Different Criteria in Parameterizing the Potential Energy Function. Fort Belvoir, VA: Defense Technical Information Center, October 1991. http://dx.doi.org/10.21236/ada242586.

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Perdigão, Rui A. P. Information Physical Artificial Intelligence in Complex System Dynamics: Breaking Frontiers in Nonlinear Analytics, Model Design and Socio-Environmental Decision Support in a Coevolutionary World. Meteoceanics, September 2020. http://dx.doi.org/10.46337/200930.

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Daudelin, Francois, Lina Taing, Lucy Chen, Claudia Abreu Lopes, Adeniyi Francis Fagbamigbe, and Hamid Mehmood. Mapping WASH-related disease risk: A review of risk concepts and methods. United Nations University Institute for Water, Environment and Health, December 2021. http://dx.doi.org/10.53328/uxuo4751.

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The report provides a review of how risk is conceived of, modelled, and mapped in studies of infectious water, sanitation, and hygiene (WASH) related diseases. It focuses on spatial epidemiology of cholera, malaria and dengue to offer recommendations for the field of WASH-related disease risk mapping. The report notes a lack of consensus on the definition of disease risk in the literature, which limits the interpretability of the resulting analyses and could affect the quality of the design and direction of public health interventions. In addition, existing risk frameworks that consider disease incidence separately from community vulnerability have conceptual overlap in their components and conflate the probability and severity of disease risk into a single component. The report identifies four methods used to develop risk maps, i) observational, ii) index-based, iii) associative modelling and iv) mechanistic modelling. Observational methods are limited by a lack of historical data sets and their assumption that historical outcomes are representative of current and future risks. The more general index-based methods offer a highly flexible approach based on observed and modelled risks and can be used for partially qualitative or difficult-to-measure indicators, such as socioeconomic vulnerability. For multidimensional risk measures, indices representing different dimensions can be aggregated to form a composite index or be considered jointly without aggregation. The latter approach can distinguish between different types of disease risk such as outbreaks of high frequency/low intensity and low frequency/high intensity. Associative models, including machine learning and artificial intelligence (AI), are commonly used to measure current risk, future risk (short-term for early warning systems) or risk in areas with low data availability, but concerns about bias, privacy, trust, and accountability in algorithms can limit their application. In addition, they typically do not account for gender and demographic variables that allow risk analyses for different vulnerable groups. As an alternative, mechanistic models can be used for similar purposes as well as to create spatial measures of disease transmission efficiency or to model risk outcomes from hypothetical scenarios. Mechanistic models, however, are limited by their inability to capture locally specific transmission dynamics. The report recommends that future WASH-related disease risk mapping research: - Conceptualise risk as a function of the probability and severity of a disease risk event. Probability and severity can be disaggregated into sub-components. For outbreak-prone diseases, probability can be represented by a likelihood component while severity can be disaggregated into transmission and sensitivity sub-components, where sensitivity represents factors affecting health and socioeconomic outcomes of infection. -Employ jointly considered unaggregated indices to map multidimensional risk. Individual indices representing multiple dimensions of risk should be developed using a range of methods to take advantage of their relative strengths. -Develop and apply collaborative approaches with public health officials, development organizations and relevant stakeholders to identify appropriate interventions and priority levels for different types of risk, while ensuring the needs and values of users are met in an ethical and socially responsible manner. -Enhance identification of vulnerable populations by further disaggregating risk estimates and accounting for demographic and behavioural variables and using novel data sources such as big data and citizen science. This review is the first to focus solely on WASH-related disease risk mapping and modelling. The recommendations can be used as a guide for developing spatial epidemiology models in tandem with public health officials and to help detect and develop tailored responses to WASH-related disease outbreaks that meet the needs of vulnerable populations. The report’s main target audience is modellers, public health authorities and partners responsible for co-designing and implementing multi-sectoral health interventions, with a particular emphasis on facilitating the integration of health and WASH services delivery contributing to Sustainable Development Goals (SDG) 3 (good health and well-being) and 6 (clean water and sanitation).
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