Academic literature on the topic 'Dynamic design of experiments'

AbstractThis PhD thesis covers multiple approaches for dynamic design of experiments considering safety constraints. Special emphasis is put on the evaluation of these methods at real-world systems in the combustion engine domain.

The rapid advancement and increasing number of applications of Unmanned Aerial Vehicle (UAV) swarm systems have garnered significant attention in recent years. These systems offer a multitude of uses and demonstrate great potential in diverse fields, ranging from surveillance and reconnaissance to search and rescue operations. However, the deployment of UAV swarms in dynamic environments necessitates the development of robust experimental designs to ensure their reliability and effectiveness. This study describes the crucial requirement for comprehensive experimental design of UAV swarm systems before their deployment in real-world scenarios. To achieve this, we begin with a concise review of existing simulation platforms, assessing their suitability for various specific needs. Through this evaluation, we identify the most appropriate tools to facilitate one’s research objectives. Subsequently, we present an experimental design process tailored for validating the resilience and performance of UAV swarm systems for accomplishing the desired objectives. Furthermore, we explore strategies to simulate various scenarios and challenges that the swarm may encounter in dynamic environments, ensuring comprehensive testing and analysis. Complex multimodal experiments may require system designs that may not be completely satisfied by a single simulation platform; thus, interoperability between simulation platforms is also examined. Overall, this paper serves as a comprehensive guide for designing swarm experiments, enabling the advancement and optimization of UAV swarm systems through validation in simulated controlled environments.

A hybrid vibration isolator (HVI) is presented with its structure, dynamic model, control strategy and preliminary experiments. The HVI is composed of the active piezostack actuator and the passive rubber isolator, which has compact structure and high reliability. Based on the dynamic model and the formula derivation of the transmissibility, the control algorithm is established using the linear quadratic regulator method. The simulations indicate that the vibrations acting on the load platform are vastly reduced, where the active piezostack-based actuator can eliminate the resonance peak significantly. Moreover, the passive rubber-based isolator is effective to isolate a part of vibration once active control fails. Finally, an experimental system is built up to implement integrated passive and active vibration control using the HVI prototype. The experimental results verify the theoretical analysis work.

The effective design and implementation of interventions that reduce vulnerability and poverty require a solid understanding of underlying poverty dynamics and associated behavioral responses. Stochastic and dynamic benefit streams can make it difficult for the poor to learn the value of such interventions to them. We explore how dynamic field experiments can help (i) intended beneficiaries to learn and understand these complicated benefit streams, and (ii) researchers to better understand how the poor respond to risk when faced with nonlinear welfare dynamics. We discuss and analyze dynamic risk valuation experiments in Morocco, Peru, and Kenya.

This paper discusses a control architecture to equip humanoid robots with dynamic manipulation skills. Such skills are beneficial, as they increase the dexterity of humanoid robots and improve their handling of unforeseen situations. The nature of manipulation poses challenges with respect to environment perception, action planning, and motion control. These challenges are addressed in the paper: a dynamic force/torque (F/T) observer is discussed to reconstruct the environment F/Ts and to improve the interaction control. A method for online motion planning is investigated, which generates trajectories based on different selection criteria. These elements are integrated in a control design for dynamic manipulation and experimentally validated for two tasks: two-handed ball throwing and one-handed ball catching. Based on the experimental results, a modified end effector design with intrinsic compliance is proposed to improve the system performance that is demonstrated in case studies.

Les manipulateurs cinématiques parallèles (PKMs) ont acquis une popularité croissante au cours des dernières décennies. Cet intérêt a été stimulé par les avantages significatifs des PKM par rapport à leurs homologues en série en matière d’accélérations élevées et de précision.Un développement de contrôles efficaces et performant joue un rôle essentiel dans l’amélioration des performances globales des PKM. Le contrôle des PKM est souvent considéré dans la littérature comme une tâche très difficile en raison de leur dynamique non linéaire, de leurs incertitudes abondantes, de la variation des paramètres et de la redondance des actionnements. Dans cette thèse, nous visons à améliorer les performances dynamiques des PKM en matière de mouvements à grande vitesse, de robustesse et de précision.Ainsi, nous proposons d’améliorer certaines stratégies de contrôle robustes (RISE et SMC supertorsion) et compenser certaines sources d’erreurs (dynamique de l’actionneur et du frottement) par des solutions de contrôle dynamique. Une analyse de stabilité à base de Lyaponuv est établie pour tous les contrôleurs proposés vérifiant la convergence asymptotique de l’erreur de suivi à zéro à mesure que le temps passe à l’infini. Afin de valider les contrôleurs proposés, des expériences en temps réel sont menées sur plusieurs prototypes de robots parallèles: robot Delta à 3 DOF a l’EPFL, en Suisse, robot VELOCE à 4DOF et robot SPIDER4 à 5 DOF au LIRMM, en France. Plusieurs scénarios sont testés, notamment les scénarios nominaux, la robustesse face aux variations de vitesses et la robustesse face aux variations de charge utile. Les méthodes de contrôle proposées vérifient leur capacité et leur capacité à améliorer les performances dynamiques des manipulateurs parallèles,en particulier lorsqu’elles fonctionnent dans des conditions dynamiques élevées(haute vitesse et charge utile gérée)
Parallel Kinematic Manipulators (PKMs) have gained an increased popularity in thelast few decades. This interest has been stimulated by the significant advantages of PKMscompared to their serial counterparts, such as better precision and higher accelerationcapabilities. Efficient and performant control algorithms play a crucial role in improvingthe overall performance of PKMs. Control of PKMs is often considered in the literature achallenging task due to their highly nonlinear dynamics, abundant uncertainties, parametersvariation, and actuation redundancy. In this thesis, we aim at improving the dynamicperformance of PKMs in terms of precision and robustness towards changes of operatingconditions. Thus, we propose robust control strategies being extensions of (i) the standardRobust Integral of the Sign of the Error (RISE) feedback control and (ii) the super-twistingSliding Mode Control (SMC). Moreover, an actuator and friction dynamics formulation isproposed within a model-based control strategy to compensate for their resulting errors.Lyaponuv-based stability analysis is established for all the proposed controllers verifyingthe asymptotic convergence of the tracking errors. In order to validate the proposed controllers,real-time experiments are conducted on several parallel robot prototypes: the 3-DOF Delta robot at EPFL, Switzerland, the 4-DOF VELOCE robot, and the 5-DOF SPIDER4robot at LIRMM, France. Several experiments are tested including nominal scenarios, robustnesstowards speed variation, and robustness towards payload changes. The relevanceof the proposed control schemes is proved through the improvement of the tracking errorsat different dynamic operating conditions

Model-based design of experiments (MBDoE) techniques are a very useful tool for the rapid assessment and development of dynamic deterministic models, providing a significant support to the model identification task on a broad range of process engineering applications. These techniques allow to maximise the information content of an experimental trial by acting on the settings of an experiment in terms of initial conditions, profiles of the manipulated inputs and number and time location of the output measurements. Despite their popularity, standard MBDoE techniques are still affected by some limitations. In fact, when a set of constraints is imposed on the system inputs or outputs, factors like uncertainty on prior parameter estimation and structural system/model mismatch may lead the design procedure to plan experiments that turn out, in practice, to be suboptimal (i.e. scarcely informative) and/or unfeasible (i.e. violating the constraints imposed on the system). Additionally, standard MBDoE techniques have been originally developed considering a discrete acquisition of the information. Therefore, they do not consider the possibility that the information on the system itself could be acquired very frequently if there was the possibility to record the system responses in a continuous manner. In this Dissertation three novel MBDoE methodologies are proposed to address the above issues. First, a strategy for the online model-based redesign of experiments is developed, where the manipulated inputs are updated while an experiment is still running. Thanks to intermediate parameter estimations, the information is exploited as soon as it is generated from an experiment, with great benefit in terms of precision and accuracy of the final parameter estimate and of experimental time. Secondly, a general methodology is proposed to formulate and solve the experiment design problem by explicitly taking into account the presence of parametric uncertainty, so as to ensure by design both feasibility and optimality of an experiment. A prediction of the system responses for the given parameter distribution is used to evaluate and update suitable backoffs from the nominal constraints, which are used in the design session in order to keep the system within a feasible region with specified probability. Finally, a design criterion particularly suitable for systems where continuous measurements are available is proposed in order to optimise the information dynamics of the experiments since the very beginning of the trial. This approach allows tailoring the design procedure to the specificity of the measurement system. A further contribution of this Dissertation is aimed at assessing the general applicability of both standard and advanced MBDoE techniques to the biomedical area, where unconventional experiment design applications are faced. In particular, two identification problems are considered: one related to the optimal drug administration in cancer chemotherapy, and one related to glucose homeostasis models for subjects affected by type 1 diabetes mellitus (T1DM). Particular attention is drawn to the optimal design of clinical tests for the parametric identification of detailed physiological models of T1DM. In this latter case, advanced MBDoE techniques are used to ensure a safe and optimally informative clinical test for model identification. The practicability and effectiveness of a complex approach taking simultaneously into account the redesign-based and the backoff-based MBDoE strategies are also shown. The proposed experiment design procedure provides alternative test protocols that are sufficiently short and easy to carry out, and allow for a precise, accurate and safe estimation of the model parameters defining the metabolic portrait of a diabetic subject.
Le moderne tecniche di progettazione ottimale degli esperimenti basata su modello (MBDoE, model-based design of experiments) si sono dimostrate utili ed efficaci per sviluppare e affinare modelli matematici dinamici di tipo deterministico. Queste tecniche consentono di massimizzare il contenuto informativo di un esperimento di identificazione, determinando le condizioni sperimentali più opportune da adottare nella sperimentazione allo scopo di stimare i parametri di un modello nel modo più rapido ed efficiente possibile. Le tecniche MBDoE sono state applicate con successo in svariate applicazioni industriali. Tuttavia, nella loro formulazione standard, esse soffrono di alcune limitazioni. Infatti, quando sussistono vincoli sugli ingressi manipolabili dallo sperimentatore oppure sulle risposte del sistema, l’incertezza nell’informazione preliminare che lo sperimentatore possiede sul sistema fisico (in termini di struttura del modello e precisione nella stima dei parametri) può profondamente influenzare l’efficacia della procedura di progettazione dell’esperimento. Come conseguenza, è possibile che venga progettato un esperimento poco informativo e dunque inadeguato per stimare i parametri del modello in maniera statisticamente precisa ed accurata, o addirittura un esperimento che porta a violare i vincoli imposti sul sistema in esame. Inoltre, le tecniche MBDoE standard non considerano nella formulazione stessa del problema di progettazione la specificità e le caratteristiche del sistema di misura in termini di frequenza, precisione e accuratezza con cui le misure sono disponibili. Nella ricerca descritta in questa Dissertazione sono sviluppate metodologie avanzate di progettazione degli esperimenti con lo scopo di superare tali limitazioni. In particolare, sono proposte tre nuove tecniche per la progettazione ottimale di esperimenti dinamici basata su modello: 1. una tecnica di progettazione in linea degli esperimenti (OMBRE, online model-based redesign of experiments), che consente di riprogettare un esperimento mentre questo è ancora in esecuzione; 2. una tecnica basata sul concetto di “backoff” (arretramento) dai vincoli, per gestire l’incertezza parametrica e strutturale del modello; 3. una tecnica di progettazione che consente di ottimizzare l’informazione dinamica di un esperimento (DMBDoE, dynamic model-based design of experiments) allo scopo di considerare la specificità del sistema di misura disponibile. La procedura standard MBDoE per la progettazione di un esperimento è sequenziale e si articola in tre stadi successivi. Nel primo stadio l’esperimento viene progettato considerando l’informazione preliminare disponibile in termini di struttura del modello e stima preliminare dei parametri. Il risultato della progettazione è una serie di profili ottimali delle variabili manipolabili (ingressi) e l’allocazione ottimale dei tempi di campionamento delle misure (uscite). Nel secondo stadio l’esperimento viene effettivamente condotto, impiegando le condizioni sperimentali progettate e raccogliendo le misure come da progetto. Nel terzo stadio, le misure vengono utilizzate per stimare i parametri del modello. Seguendo questa procedura, l’informazione ottenuta dall’esperimento viene sfruttata solo a conclusione dell’esperimento stesso. La tecnica OMBRE proposta consente invece di riprogettare l’esperimento, e quindi di aggiornare i profili manipolabili nel tempo, mentre l’esperimento è ancora in esecuzione, attuando stime intermedie dei parametri. In questo modo l’informazione viene sfruttata progressivamente mano a mano che l’esperimento procede. I vantaggi di questa tecnica sono molteplici. Prima di tutto, la procedura di progettazione diventa meno sensibile, rispetto alla procedura standard, alla qualità della stima preliminare dei parametri. In secondo luogo, essa consente una stima dei parametri statisticamente più soddisfacente, grazie alla possibilità di sfruttare in modo progressivo l’informazione generata dall’esperimento. Inoltre, la tecnica OMBRE consente di ridurre le dimensioni del problema di ottimizzazione, con grande beneficio in termini di robustezza computazionale. In alcune applicazioni, risulta di importanza critica garantire la fattibilità dell’esperimento, ossia l’osservanza dei vincoli imposti sul sistema. Nella Dissertazione è proposta e illustrata una nuova procedura di progettazione degli esperimenti basata sul concetto di “backoff” (arretramento) dai vincoli, nella quale l’effetto dell’incertezza sulla stima dei parametri e/o l’inadeguatezza strutturale del modello vengono inclusi nella formulazione delle equazioni di vincolo grazie ad una simulazione stocastica. Questo approccio porta a ridurre lo spazio utile per la progettazione dell’esperimento in modo tale da assicurare che le condizioni di progettazione siano in grado di garantire non solo l’identificazione dei parametri del modello, ma anche la fattibilità dell’esperimento in presenza di incertezza strutturale e/o parametrica del modello. Nelle tecniche standard di progettazione la formulazione del problema di ottimo prevede che le misure vengano acquisite in maniera discreta, considerando una certa distanza temporale tra misure successive. Di conseguenza, l’informazione attesa dall’esperimento viene calcolata e massimizzata durante la progettazione mediante una misura discreta dell’informazione di Fisher. Tuttavia, nella pratica, sistemi di misura di tipo continuo permetterebbero di seguire la dinamica del processo mediante misurazioni molto frequenti. Per questo motivo viene proposto un nuovo criterio di progettazione (DMBDoE), nel quale l’informazione attesa dall’esperimento viene ottimizzata in maniera continua. Il nuovo approccio consente di generalizzare l’approccio della progettazione includendo le caratteristiche del sistema di misura (in termini di frequenza di campionamento, accuratezza e precisione delle misure) nella formulazione stessa del problema di ottimo. Un ulteriore contributo della ricerca presentata in questa Dissertazione è l’estensione al settore biomedico di tecniche MBDoE standard ed avanzate. I sistemi fisiologici sono caratterizzati da elevata complessità, e spesso da scarsa controllabilità e scarsa osservabilità. Questi elementi rendono particolarmente lunghe e complesse le procedure di identificazione parametrica di modelli fisiologici dettagliati. L’attività di ricerca ha considerato due problemi principali inerenti l’identificazione parametrica di modelli fisiologici: il primo legato a un modello per la somministrazione ottimale di agenti chemioterapici per la cura del cancro, il secondo relativo ai modelli complessi dell’omeostasi glucidica per soggetti affetti da diabete mellito di tipo 1. In quest’ultimo caso, al quale è rivolta attenzione particolare, l’obiettivo principale è identificare il set di parametri individuali del soggetto diabetico. Ciò consente di tracciarne un ritratto metabolico, fornendo così un prezioso supporto qualora si intenda utilizzare il modello per sviluppare e verificare algoritmi avanzati per il controllo del diabete di tipo 1. Nella letteratura e nella pratica medica esistono test clinici standard, quali il test orale di tolleranza al glucosio e il test post-prandiale da carico di glucosio, per la diagnostica del diabete e l’identificazione di modelli dell’omeostasi glucidica. Tali test sono sufficientemente brevi e sicuri per il soggetto diabetico, ma si possono rivelare poco informativi quando l’obiettivo è quello di identificare i parametri di modelli complessi del diabete. L’eccitazione fornita durante questi test al sistema-soggetto, in termini di infusione di insulina e somministrazione di glucosio, può infatti essere insufficiente per stimare in maniera statisticamente soddisfacente i parametri del modello. In questa Dissertazione è proposto l’impiego di tecniche MBDoE standard e avanzate per progettare test clinici che permettano di identificare nel modo più rapido ed efficiente possibile il set di parametri che caratterizzano un soggetto affetto da diabete, rispettando durante il test i vincoli imposti sul livello glicemico del soggetto. Partendo dai test standard per l’identificazione di modelli fisiologici del diabete, è così possibile determinare dei protocolli clinici modificati in grado di garantire test clinici altamente informativi, sicuri, poco invasivi e sufficientemente brevi. In particolare, si mostra come un test orale opportunamente modificato risulta altamente informativo per l’identificazione, sicuro per il paziente e di facile implementazione per il clinico. Inoltre, viene evidenziato come l’integrazione di tecniche avanzate di progettazione (quali OMBRE e tecniche basate sul concetto di backoff) è in grado di garantire elevata significatività e sicurezza dei test clinici anche in presenza di incertezza strutturale, oltre che parametrica, del modello. Infine, si mostra come, qualora siano disponibili misure molto frequenti della glicemia, ottimizzare mediante tecniche DMBDoE l’informazione dinamica progressivamente acquisita dal sistema di misura durante il test consente di sviluppare protocolli clinici altamente informativi, ma di durata inferiore, minimizzando così lo stress sul soggetto diabetico. La struttura della Dissertazione è la seguente. Il primo Capitolo illustra lo stato dell’arte delle attuali tecniche di progettazione ottimale degli esperimenti, analizzandone le limitazioni e identificando gli obiettivi della ricerca. Il secondo Capitolo contiene la trattazione matematica necessaria per comprendere la procedure standard di progettazione degli esperimenti. Il terzo Capitolo presenta la nuova tecnica OMBRE per la riprogettazione in linea di esperimenti dinamici. La tecnica viene applicata a due casi di studio, riguardanti un processo di fermentazione di biomassa in un reattore semicontinuo e un processo per la produzione di uretano. Il quarto Capitolo propone e illustra il metodo basato sul concetto di “backoff” per gestire l’effetto dell’incertezza parametrica e strutturale nella formulazione stessa del problema di progettazione. L’efficacia del metodo è verificata su due casi di studio in ambito biomedico. Il primo riguarda l’ottimizzazione dell’infusione di insulina per l’identificazione di un modello dettagliato del diabete mellito di tipo 1; il secondo la somministrazione ottimale di agenti chemioterapici per la cura del cancro. Il quinto Capitolo riguarda interamente il problema della progettazione ottimale di test clinici per l’identificazione di un modello fisiologico complesso del diabete mellito di tipo 1. La progettazione di protocolli clinici modificati avviene adottando tecniche MBDoE in presenza di elevata incertezza parametrica tra modello e soggetto diabetico. Il sesto Capitolo affronta il problema della progettazione dei test clinici assumendo sia incertezza di modello parametrica che strutturale. Il settimo Capitolo propone un nuovo criterio di progettazione (DMBDoE) che ottimizza l’informazione dinamica acquisibile da un esperimento. La tecnica viene applicata a un modello complesso del diabete mellito di tipo 1 e ad un processo per la fermentazione di biomassa in un reattore semicontinuo. Conclusioni e possibili sviluppi futuri vengono descritti nella sezione conclusiva della Dissertazione.

Public health data show the tremendous economic and societal impact of pandemic influenza in the past. Currently, the welfare of society is threatened by the lack of planning to ensure an adequate response to a pandemic. This preparation is difficult because the characteristics of the virus that would cause the pandemic are unknown, but primarily because the response requires tools to support decision-making based on scientific methods. The response to the next pandemic influenza will likely include extensive use of antiviral drugs, which will create an unprecedented selective pressure for the emergence of antiviral resistant strains. Nevertheless, the literature has insufficient exhaustive models to simulate the spread and mitigation of pandemic influenza, including infection by an antiviral resistant strain. We are building a large-scale simulation optimization framework for development of dynamic antiviral strategies including treatment of symptomatic cases and chemoprophylaxis of pre- and post-exposure cases. The model considers an oseltamivir-sensitive strain and a resistant strain with low/high fitness cost, induced by the use of the several antiviral measures. The mitigation strategies incorporate age/immunitybased risk groups for treatment and pre-/post-exposure chemoprophylaxis, and duration of pre-exposure chemoprophylaxis. The model is tested on a hypothetical region in Florida, U.S., involving more than one million people. The analysis is conducted under different virus transmissibility and severity scenarios, varying intensity of non-pharmaceutical interventions, measuring the levels of antiviral stockpile availability. The model is intended to support pandemic preparedness and response policy making.

Engine thermal and lubricant systems have only recently been a serious focus in engine design and in general remain under passive control. The introduction of active control has shown benefits in fuel consumption during the engine warm-up period, however there is a lack of rigorous calibration of these devices in conjunction with other engine systems. For these systems, benefits in fuel consumption (FC) are small and accurate measurement systems are required. Analysis of both FC and NOx emissions measurements processes was conducted and showed typical errors of 1% in FC from thermal expansion and 2% in NOx per g/kg change in absolute humidity. Correction factors were derived both empirically and from first principles to account for these disturbances. These improvements are applicable to the majority of experimental facilities and will be essential as future engine developments are expected to be achieved through small incremental steps. Using prototype hardware installed on a production 2.4L Diesel engine, methodologies for optimising the design, control and integration of these systems were demonstrated. Design of experiments (DoE) based approaches were used to model the engine behaviour under transient conditions. A subsequent optimisation procedure demonstrated a 3.2% reduction in FC during warm-up from 25°C under iso-NOx conditions. This complemented a 4% reduction from reduced oil pumping work using a variable displacement pump. A combination of classical DoE and transient testing allowed the dynamic behaviour of the engine to be captured empirically when prototype hardware is available. Furthermore, the enhancement of dynamic DoE approaches to include the thermal condition of the engine can produce models that, when combined with other available simulation packages, offer a tool for design optimisation when hardware is not available. These modelling approaches are applicable to a wide number of problems to evaluate design considerations at different stages of the engine development process. These allow the transient thermal behaviour of the engine to be captured, significantly enhancing conventional model based calibration approaches.

Plasma railguns are electromagnetic accelerators used to produce controlled high velocity plasma jets. This thesis discusses the design and characterization of a small coaxial plasma railgun intended to accelerate argon-helium plasma jets. The railgun will be used for the study of plasma shocks in jet collisions. The railgun is mounted on a KF-40 vacuum port and operated using a 90 kA, 11 kV LC pulse forming network. Existing knowledge of coaxial railgun plasma instabilities and material interactions at vacuum and plasma interfaces are applied to the design. The design of individual gun components is detailed. Jet velocity and density are characterized by analyzing diagnostic data collected from a Rogowski coil, interferometer, and photodiode. Peak line-integrated electron number densities of approximately 8 × 10¹⁵ cm^-2 and jet velocities of tens of km/s are inferred from the data recorded from ten experimental pulses.
Master of Science
Plasma is a gaseous state of matter which is electrically conductive and interacts with electric and magnetic fields. Plasmas are used in many everyday objects such as fluorescent lights, but some of the physics of plasmas are still not entirely understood. One set of plasma interactions that have not been fully explored are those which occur during high-velocity collisions between plasmas. Experiments aimed to further the understanding of these interactions require the generation of plasmas with specified properties at very high velocities. A device known as a plasma railgun can be used to produce plasmas which meet these experimental demands. In a plasma railgun, a short pulse of current is passed through a plasma located between two parallel electrodes, or "rails". This current generates a magnetic field which propels the plasma forward. The plasma is accelerated until it leaves the muzzle of the railgun. In coaxial plasma railguns, the electrodes are concentric. This paper discusses the design and testing of a small, relatively low power coaxial plasma railgun. Specific elements of the design are examined and the inherent physical and material difficulties of a coaxial design are explored. The experiment which was performed to confirm the properties of the plasma jets produced by the coaxial plasma railgun is explained. The results of this experiment confirm that the design succeeds in producing plasmas which meet targets for plasma properties.

Experiments have been conducted to investigate the fracture and fragmentation characteristics of a liquid phased sintered (LPS) tungsten and high strength steel alloys. Metal cylinders, each of which was 20.32 cm tall and 5.08 cm inner/5.88 cm outer diameter, were explosively driven to failure. Two complimentary types of experiments were conducted in this series to determine input parameters for a related continuum mechanics based modeling effort. Open air experiments utilized ultra-high speed framing photography and a photonic Doppler velocimetry system (PDV). The information from these experiments provided a case wall velocity, relative time of breakup and strain-rate during the stress loading timeframe. Complimentary experiments were conducted in a water tank to perform a soft recovery of the fragments. The fragments were subsequently cleaned, massed, and characterized according to their mass and failure strain distributions. Various methods of analyzing the data (Mott & Weibull distributions) are discussed along with the calibration of the continuum damage model parameters. Results of the failure strain analysis, fragment distribution, and damage model are then supplied for use in subsequent modeling and application designs. Further details of the modeling and simulation approach are outlined in a complimentary set of two papers presented by Lambert [1] and Hopson [2].

Abstract Using forward and inverse dynamic analysis, the dynamic simulation of a backhoe has been compared with experiments. In the experiment, recorded were the configuration and force histories; that is, velocity and position, and force output from the hydraulic cylinder-all were measured in the time domain. When the experimental force history is used as driving force in the simulation, forward dynamic analysis produces a corresponding motion history. And when the experimental motion history is used as if a prescribed trajectory, inverse dynamic analysis generates a corresponding force history. Therefore, these two sets of motion and force histories — one set from experiment, and the other from the simulation that is driven forward and backward with the experimental data — are compared in the time domain. The comparisons are discussed in regard to the effects of variations in initial conditions, friction, and viscous damping.

The performance of an aircraft in flight is, in part, a result of interactions between aerodynamic forces and structural deformations. Aerodynamic pressures result in elastic deformations which alter the wing shape and thus affect the aerodynamics. Consideration of this multidisciplinary interaction is critical to wing design. In particular, divergence (static elastic instability) and flutter (dynamic resonance) are potential catastrophic effects to be avoided. Performing an aeroelastic analysis requires the combination of static and dynamic structural analysis (often done through finite element analysis) with aerodynamic analysis (typically using some form of computational fluid dynamics, CFD). For large grids, each of these can require a significant computational effort. Resolving the interactions between the two is an iterative process which only magnifies the problem. This is a typical characteristic and drawback of multidisciplinary analysis; it makes exploring a large design space (which may include a large range of wing shape, structural support, and material choices) particularly challenging. Statistical design of experiments (DOX) is one technique for design space exploration using a limited number of targeted, computational experiments. DOX is useful for identifying the design variables most critical for a relevant response, and for finding sensitivities needed for design optimization. The objectives for this project were (1) to find the most significant geometric, modeling, and material parameters that affect the predicted aeroelastic responses of a simple wing geometry, (2) to develop parsimonious, low-order response surfaces to model effects of interest, (3) and to evaluate the quality of the response surfaces. The computational experiments were performed with MSC Nastran which combines finite element analysis for the structural response with a steady vortex-lattice method for trim aeroelastic analyses. The discussion will include an overview of the experiment design selection process, formulation of an approximation model, and an explanation of key metrics for evaluating the response surface designs. Comprehensive results are presented for the natural frequency responses, as well as a preliminary analysis of aerodynamic trim solutions.

Uniaxial tensile tests were conducted on American Society for Testing Materials International (ASTM) A992 and A572 Grade 50 steels at increasing strain rates to determine the material strength properties of structural members subjected to dynamic loadings. The increase in dynamic yield strength and ultimate tensile strength was determined to update design criteria within UFC 3-340-02, which are currently limited to ASTM A36 and A514 steels. The proposed updates will provide the necessary information required to design blast-resistant structures utilizing modern-day structural steels. The dynamic material properties determined by high-rate tensile tests were compared to static values obtained from ASTM E8 standard tensile tests. The comparisons were used to calculate dynamic increase factors (DIFs) for each steel at strain rates from 2E-3 to 2E0 inch/inch/second. The experiments revealed that the A992 steel exhibited an increase in yield strength up to 45% and ultimate tensile strength up to 20% as strain rate increased over the range tested. The A572-50 steel exhibited a similar increase in yield strength up to 35% and ultimate tensile strength up to 20%. The DIF design curves developed during this research will allow engineers to more efficiently design structural steel components of hardened structures for the protection of our nation’s critical infrastructure.

Regulatory experiments can be useful to guide complex transitions in the field of sustainable development. They help to understand the effects of policies and regulations and offer insights into the dynamics of social processes. Empirical studies analyzing heterogeneous samples of regulatory experiments are missing. This paper uses a qualitative content analysis to examine 26 international cases of regulatory experiments in the field of sustainable development. The results show the diversity of existing regulatory experiments in terms of their design. We use the results to formulate implications on how to use regulatory experiments that facilitate learning processes.

A thermowell design standard published by ASME was recently updated to incorporate new knowledge about dynamic loads on thermowells and other factors affecting thermowell integrity and measurement accuracy. There are concerns that assumptions in the ASME standard may cause significant measurement inaccuracies or conservative designs that require significant changes to natural gas installations. To avoid thermowell damage and measure natural gas temperatures accurately, pipeline operators have requested additional guidance on thermowell design and installation. This study investigated current thermowell standards and research to provide PRCI members, meter station designers, and the natural gas industry with guidelines to design thermowells that meet accuracy and integrity requirements. Relevant design requirements from ASME and other thermowell standards were examined to summarize and compare insertion length requirements, recommended materials, and guidance for temperature accuracy. Research publications were reviewed for experimental data to identify design parameters that affect thermowell integrity and measurement accuracy, and to determine whether separate natural gas design guidelines could be developed or whether modifications should be recommended to the ASME procedure. Priority was given to experimental results over analytical and computational data. The review also focused on thermowell performance in natural gas at transmission pipeline conditions, defined here as pressures up to 1,800 psig (124 barg) and flow velocities up to 125 ft/s (38 m/s). Key design parameters were identified that can be used as a starting point for a natural gas thermowell design and installation procedure. A gap analysis identified further research needs for thermowell performance in natural gas service.

Over the last decade there has been a dramatic shift in global agricultural practice. The increase in human population, especially in underdeveloped arid and semiarid regions of the world, poses unprecedented challenges to production of an adequate and economically feasible food supply to undernourished populations. Furthermore, the increased living standard in many industrial countries has created a strong demand for high-quality, out-of-season vegetables and fruits as well as for ornamentals such as cut and potted flowers and bedding plants. As a response to these imminent challenges and demands and because of a ban on methyl bromide fumigation of horticultural field soils, soilless greenhouse production systems are regaining increased worldwide attention. Though there is considerable recent empirical and theoretical research devoted to specific issues related to control and management of soilless culture production systems, a comprehensive approach that quantitatively considers all relevant physicochemical processes within the growth substrates is lacking. Moreover, it is common practice to treat soilless growth systems as static, ignoring dynamic changes of important physicochemical and hydraulic properties due to root and microbial growth that require adaptation of management practices throughout the growth period. To overcome these shortcomings, the objectives of this project were to apply thorough physicochemical characterization of commonly used greenhouse substrates in conjunction with state-of-the-art numerical modeling (HYDRUS-3D, PARSWMS) to not only optimize management practices (i.e., irrigation frequency and rates, fertigation, container size and geometry, etc.), but to also “engineer” optimal substrates by mixing organic (e.g., coconut coir) and inorganic (e.g., perlite, pumice, etc.) base substrates and modifying relevant parameters such as the particle (aggregate) size distribution. To evaluate the proposed approach under commercial production conditions, characterization and modeling efforts were accompanied by greenhouse experiments with tomatoes. The project not only yielded novel insights regarding favorable physicochemical properties of advanced greenhouse substrates, but also provided critically needed tools for control and management of containerized soilless production systems to provide a stress-free rhizosphere environment for optimal yields, while conserving valuable production resources. Numerical modeling results provided a more scientifically sound basis for the design of commercial greenhouse production trials and selection of adequate plant-specific substrates, thereby alleviating the risk of costly mistrials.

This project evaluated current end treatment designs that are used in the natural gas industry and used Computational Fluid Dynamics (CFD) to determine the end treatment with the best flow characteristics when installed upstream from an ultrasonic flow meter. The project team optimized the end treatment design and additional CFD and experimental testing was conducted. The experimental results of the developed end treatment were shown to provide results within ±0.25% relative to the baseline configuration with various inlet conditions and numbers of ultrasonic paths.

This project evaluated current end treatment designs that are used in the natural gas industry and used Computational Fluid Dynamics (CFD) to determine the end treatment with the best flow characteristics when installed upstream from an ultrasonic flow meter. The project team optimized the end treatment design and additional CFD and experimental testing was conducted. The experimental results of the developed end treatment were shown to provide results within �0.25% relative to the baseline configuration with various inlet conditions and numbers of ultrasonic paths.

The purpose of this project was to complete a handbook with practical design procedures for submarine pipeline on-bottom stability. The remaining part of the handbook was primarily a description of the interaction between non-trenched pipelines and the seabed where the pipelines were free to move under environmental loading. The objective of this project was to determine the lateral soil resistance forces on a pipeline moving cyclically during hydro-dynamic loading. To meet the goal, full-scale pipe-soil interaction tests were conducted. The models presented in this report are based on the results and general understanding obtained from 110 experimental tests of pipe-soil interaction on loose and dense sand, and soft clay. Raw data from 29 experimental tests on stiff clay in the PIPESTAB project have been qualitatively considered.