<p>    </p> <p>Irregular control-flow structures like deeply nested conditional branches are common in real-world software applications. Improving the performance and efficiency of such programs is often challenging because it is difficult to analyze and optimize programs with irregular control flow. We observe that real-world programs contain similar or identical computations within different code paths of the conditional branches. Compilers can merge similar code to improve performance or code size. However, existing compiler optimizations like code hoisting/sinking, and tail merging do not fully exploit this opportunity. We propose a new technique called Control-Flow Melding (CFM) that can merge similar code sequences at the control-flow region level. We evaluate CFM in two applications. First, we show that CFM reduces the control divergence in GPU programs and improves the performance. Second, we apply CFM to CPU programs and show its effectiveness in reducing code size without sacrificing performance. In the next part of this dissertation, we investigate how CFM can be extended to improve dynamic test generation techniques like Dynamic Symbolic Execution (DSE). DSE suffers from path explosion problem when many conditional branches are present in the program. We propose a non-semantics-preserving branch elimination transformation called CFM-SE that reduces the number of symbolic branches in a program. We also provide a framework for detecting and reasoning about false positive bugs that might be added to the program by non-semantics-preserving transformations like CFM-SE. Furthermore, we evaluate CFM-SE on real-world applications and show its effectiveness in improving DSE performance and code coverage. </p>

More dynamic markets, shorter product life cycles and comprehensive variant management are challenges that dominate today's market. These maxims apply to the automotive sector, which is currently highly exposed to trade wars, changing mobility patterns and the emergence of new technologies and competitors. To meet these challenges, this thesis presents the creation of a digital twin of an existing production line of electric motors using discrete event simulation. Based on a detailed literature research, a step-by-step establishment of the simulation model of the production line using the software Plant Simulation is presented and argued. Finally, different experiments are carried out with the created model to show how a production line can be examined and optimized by means ofsimulation using different parameters. Within the scope of the different experiments regarding the number of workpiece carriers, number of operators as well as buffer sizes, the line was examined concerning the increase of the output. Furthermore, the simulation model was used to make decisions for future investments in additional XXX machines. Four different scenarios were examined and optimized. By examining the different parameters, optimization potentials of XXX% in the first scenario and up to XXX% in the fourth scenario were achieved. Finally, it was proven that the developed simulation model can be used as a tool for optimizing an existing production line and can generate useful investment information. Beyond that, the development of the simulation model can be employed to investigate further business questions at hand for the specific production line in question. / Mer dynamiska marknader, kortare produktlivscykler och omfattande varianthantering är utmaningar som dominerar dagens marknad. Dessa maximer gäller bilindustrin, som för närvarande är mycket utsatt för handelskrig, förändrade rörlighetsmönster och framväxten av ny teknik och nya konkurrenter. För att möta dessa utmaningar innebär denna avhandling skapandet av en digital tvilling av en befintlig produktionslinje av elmotorer med diskret händelsesimulering. Baserat på en detaljerad litteraturforskning presenteras och argumenteras en steg-för-steg-etablering av simuleringsmodellen för produktionslinjen med hjälp av programvaran Plant Simulation. Slutligen utförs olika experiment med den skapade modellen för att visa hur en produktionslinje kan undersökas och optimeras med hjälp av simulering med hjälp av olika parametrar. Inom ramen för de olika experimenten när det gäller antalet arbetsstyckesbärare, antalet operatörer samt buffertstorlekar undersöktes linjen om ökningen av produktionen. Dessutom användes simuleringsmodellen för att fatta beslut för framtida investeringar i ytterligare hårnålsmaskiner. Fyra olika scenarier undersöktes och optimerades. Genom att undersöka de olika parametrarna uppnåddes optimeringspotentialer på XXX % i det första scenariot och upp till XXX % i det fjärde scenariot. Slutligen bevisades det att den utvecklade simuleringsmodellen kan användas som ett verktyg för att optimera en befintlig produktionslinje och kan generera användbar investeringsinformation. Utöver detta kan utvecklingen av simuleringsmodellen användas för att undersöka ytterligare affärsfrågor till hands för den specifika produktionslinjen i fråga.

<div>Adsorbent technology is widely used in many industrial applications including waste heat recovery, water purification, and atmospheric revitalization in confined habitations. Astronauts depend on adsorbent-based systems to remove metabolic carbon dioxide (CO₂) from the cabin atmosphere; as NASA prepares for the journey to Mars, engineers are redesigning the adsorbent-based system for reduced weight and optimal efficiency. These efforts hinge upon the development of accurate, predictive models, as simulations are increasingly relied upon to save cost and time over the traditional design-build-test approach. Engineers rely on simplified models to reduce computational cost and enable parametric optimizations. Amongst these simplified models is the axially dispersed plug-flow model for predicting the adsorbate concentration during flow through an adsorbent bed. This model is ubiquitously used in designing fixed-bed adsorption systems. The current work aims to improve the accuracy of the axially dispersed plug-flow model because of its wide-spread use. This dissertation identifies the critical model inputs that drive the overall uncertainty in important output quantities then systematically improves the measurement and prediction of these input parameters. Limitations of the axially dispersed plug-flow model are also discussed, and recommendations made for identifying failure of the plug-flow assumption.</div><div><br></div><div>An uncertainty and sensitivity analysis of an axially disperse plug-flow model is first presented. Upper and lower uncertainty bounds for each of the model inputs are found by comparing empirical correlations against experimental data from the literature. Model uncertainty is then investigated by independently varying each model input between its individual upper and lower uncertainty bounds then observing the relative change in predicted effluent concentration and temperature (<i>e.g.</i>, breakthrough time, bed capacity, and effluent temperature). This analysis showed that the LDF mass transfer coefficient is the largest source of uncertainty. Furthermore, the uncertainty analysis reveals that ignoring the effect of wall-channeling on apparent axial dispersion can cause significant error in the predicted breakthrough times of small-diameter beds.</div><div><br></div><div>In addition to LDF mass transfer coefficient and axial-dispersion, equilibrium isotherms are known to be strong lever arms and a potentially dominant source of model error. As such, detailed analysis of the equilibrium adsorption isotherms for zeolite 13X was conducted to improve the fidelity of CO₂ and H₂O on equilibrium isotherms compared to extant data. These two adsorbent/adsorbate pairs are of great interest as NASA plans to use zeolite 13X in the next generation atmospheric revitalization system. Equilibrium isotherms describe a sorbent’s maximum capacity at a given temperature and adsorbate (<i>e.g.</i>, CO₂ or H₂O) partial pressure. New isotherm data from NASA Ames Research Center and NASA Marshall Space Flight Center for CO₂ and H₂O adsorption on zeolite 13X are presented. These measurements were carefully collected to eliminate sources of bias in previous data from the literature, where incomplete activation resulted in a reduced capacity. Several models are fit to the new equilibrium isotherm data and recommendations of the best model fit are made. The best-fit isotherm models from this analysis are used in all subsequent modeling efforts discussed in this dissertation.</div><div><br></div><div>The last two chapters examine the limitations of the axially disperse plug-flow model for predicting breakthrough in confined geometries. When a bed of pellets is confined in a rigid container, packing heterogeneities near the wall lead to faster flow around the periphery of the bed (<i>i.e.</i>, wall channeling). Wall-channeling effects have long been considered negligible for beds which hold more than 20 pellets across; however, the present work shows that neglecting wall-channeling effects on dispersion can yield significant errors in model predictions. There is a fundamental gap in understanding the mechanisms which control wall-channeling driven dispersion. Furthermore, there is currently no way to predict wall channeling effects a priori or even to identify what systems will be impacted by it. This dissertation aims to fill this gap using both experimental measurements and simulations to identify mechanisms which cause the plug-flow assumption to fail.</div><div><br></div><div>First, experimental evidence of wall-channeling in beds, even at large bed-to-pellet diameter ratios (<i>d</i>_bed/<i>d</i>_p=48) is presented. These experiments are then used to validate a method for accurately extracting mass transfer coefficients from data affected by significant wall channeling. The relative magnitudes of wall-channeling effects are shown to be a function of the adsorption/adsorbate pair and geometric confinement (<i>i.e.</i>, bed size). Ultimately, the axially disperse plug-flow model fails to capture the physics of breakthrough when nonplug-flow conditions prevail in the bed.</div><div><br></div><div>The final chapter of this dissertation develops a two-dimensional (2-D) adsorption model to examine the interplay of wall-channeling and adsorption kinetics and the adsorbent equilibrium capacity on breakthrough in confined geometries. The 2-D model incorporates the effect of radial variations in porosity on the velocity profile and is shown to accurately capture the effect of wall-channeling on adsorption behavior. The 2-D model is validated against experimental data, and then used to investigate whether capacity or adsorption kinetics cause certain adsorbates to exhibit more significant radial variations in concentration compared than others. This work explains channeling effects can vary for different adsorbate and/or adsorbent pairs—even under otherwise identical conditions—and highlights the importance of considering adsorption kinetics in addition to the traditional <i>d</i>_bed/<i>d</i>_p criteria.</div><div><br></div><div>This dissertation investigates key gaps in our understanding of fixed-bed adsorption. It will deliver insight into how these missing pieces impact the accuracy of predictive models and provide a means for reconciling these errors. The culmination of this work will be an accurate, predictive model that assists in the simulation-based design of the next-generation atmospheric revitalization system for humans’ journey to Mars.</div>

Les langages dédiés de modélisation (DSMLs) sont de plus en plus utilisés dans les phases amont du développement des systèmes complexes, en particulier pour les systèmes critiques embarqués. L’objectif est de pouvoir raisonner très tôt dans le développement sur ces modèles et, notamment, de conduire des activités de vérification et validation (V and V). Une technique très utilisée est la vérification des modèles comportementaux par exploration exhaustive (model-checking) en utilisant une sémantique de traduction pour construire un modèle formel à partir des modèles métiers pour réutiliser les outils performants disponibles pour les modèles formels. Définir cette sémantique de traduction, exprimer les propriétés formelles à vérifier et analyser les résultats nécessite une expertise dans les méthodes formelles qui freine leur adoption et peut rebuter les concepteurs. Il est donc nécessaire de construire pour chaque DSML, une chaîne d’outils qui masque les aspects formels aux utilisateurs. L’objectif de cette thèse est de faciliter le développement de telles chaînes de vérification. Notre contribution inclut 1) l’expression des propriétés comportementales au niveau métier en s’appuyant sur TOCL (Temporal Object Constraint Language), une extension temporelle du langage OCL; 2) la transformation automatique de ces propriétés en propriétés formelles en réutilisant les éléments clés de la sémantique de traduction; 3) la remontée des résultats de vérification grâce à une transformation d’ordre supérieur et un langage de description de correspondance entre le domaine métier et le domaine formel et 4) le processus associé de mise en oeuvre. Notre approche a été validée par l’expérimentation sur un sous-ensemble du langage de modélisation de processus de développement SPEM, et sur le langage de commande d’automates programmables Ladder Diagram, ainsi que par l’intégration d’un langage formel intermédiaire (FIACRE) dans la chaîne outillée de vérification. Ce dernier point permet de réduire l’écart sémantique entre les DSMLs et les domaines formels. / Domain specific Modeling Languages (DSMLs) are increasingly used at the early phases in the development of complex systems, in particular, for safety critical systems. The goal is to be able to reason early in the development on these models and, in particular, to fulfill verification and validation activities (V and V). A widely used technique is the exhaustive behavioral model verification using model-checking by providing a translational semantics to build a formal model from DSML conforming models in order to reuse powerful tools available for this formal domain. Defining a translational semantics, expressing formal properties to be assessed and analysing such verification results require such an expertise in formal methods that it restricts their adoption and may discourage the designers. It is thus necessary to build for each DSML, a toolchain which hides formal aspects for DSML end-users. The goal of this thesis consists in easing the development of such verification toolchains. Our contribution includes 1) expressing behavioral properties in the DSML level by relying on TOCL (Temporal Object Constraint Language), a temporal extension of OCL; 2) An automated transformation of these properties on formal properties while reusing the key elements of the translational semantics; 3) the feedback of verification results thanks to a higher-order transformation and a language which defines mappings between DSML and formal levels; 4) the associated process implementation. Our approach was validated by the experimentation on a subset of the development process modeling language SPEM, and on Ladder Diagram language used to specify programmable logic controllers (PLCs), and by the integration of a formal intermediate language (FIACRE) in the verification toolchain. This last point allows to reduce the semantic gap between DSMLs and formal domains.

Les applications réactives et sensibles au contexte sont des applications intelligentes qui observent l’environnement (ou contexte) dans lequel elles s’exécutent et qui adaptent, si nécessaire, leur comportement en cas de changements dans ce contexte, ou afin de satisfaire les besoins ou d'anticiper les intentions des utilisateurs. La recherche dans ce domaine suscite un intérêt considérable tant de la part des académiques que des industriels. Les domaines d'applications sont nombreux: robots industriels qui peuvent détecter les changements dans l'environnement de travail de l'usine pour adapter leurs opérations; systèmes de contrôle automobiles pour observer d'autres véhicules, détecter les obstacles, ou surveiller le niveau d'essence ou de la qualité de l'air afin d'avertir les conducteurs en cas d'urgence; systèmes embarqués monitorant la puissance énergétique disponible et modifiant la consommation en conséquence. Dans la pratique, le succès de la mise en œuvre et du déploiement de systèmes sensibles au contexte dépend principalement du mécanisme de reconnaissance et de réaction aux variations de l'environnement. En d'autres termes, il est nécessaire d'avoir une approche adaptative bien définie et efficace de sorte que le comportement des systèmes peut être modifié dynamiquement à l'exécution. En outre, la concurrence devrait être exploitée pour améliorer les performances et la réactivité des systèmes. Tous ces exigences, ainsi que les besoins en sécurité et fiabilité constituent un grand défi pour les développeurs.C’est pour permettre une écriture plus intuitive et directe d'applications réactives et sensibles au contexte que nous avons développé dans cette thèse un nouveau langage appelé INI. Pour observer les changements dans le contexte et y réagir, INI s’appuie sur deux paradigmes : la programmation événementielle et la programmation à base de règles. Événements et règles peuvent être définis en INI de manière indépendante ou en combinaison. En outre, les événements peuvent être reconfigurésdynamiquement au cours de l’exécution. Un autre avantage d’INI est qu’il supporte laconcurrence afin de gérer plusieurs tâches en parallèle et ainsi améliorer les performances et la réactivité des programmes. Nous avons utilisé INI dans deux études de cas : une passerelle M2M multimédia et un programme de suivi d’objet pour le robot humanoïde Nao. Enfin, afin d’augmenter la fiabilité des programmes écrits en INI, un système de typage fort a été développé, et la sémantique opérationnelle d’INI a été entièrement définie. Nous avons en outre développé un outil appelé INICheck qui permet de convertir automatiquement un sous-ensemble d’INI vers Promela pour permettre un analyse par model checking à l’aide de l’interpréteur SPIN. / Context-aware pervasive computing has attracted a significant research interest from both academy and industry worldwide. It covers a broad range of applications that support many manufacturing and daily life activities. For instance, industrial robots detect the changes of the working environment in the factory to adapt their operations to the requirements. Automotive control systems may observe other vehicles, detect obstacles, and monitor the essence level or the air quality in order to warn the drivers in case of emergency. Another example is power-aware embedded systems that need to work based on current power/energy availability since power consumption is an important issue. Those kinds of systems can also be considered as smart applications. In practice, successful implementation and deployment of context-aware systems depend on the mechanism to recognize and react to variabilities happening in the environment. In other words, we need a well-defined and efficient adaptation approach so that the systems' behavior can be dynamically customized at runtime. Moreover, concurrency should be exploited to improve the performance and responsiveness of the systems. All those requirements, along with the need for safety, dependability, and reliability pose a big challenge for developers.In this thesis, we propose a novel programming language called INI, which supports both event-based and rule-based programming paradigms and is suitable for building concurrent and context-aware reactive applications. In our language, both events and rules can be defined explicitly, in a stand-alone way or in combination. Events in INI run in parallel (synchronously or asynchronously) in order to handle multiple tasks concurrently and may trigger the actions defined in rules. Besides, events can interact with the execution environment to adjust their behavior if necessary and respond to unpredictable changes. We apply INI in both academic and industrial case studies, namely an object tracking program running on the humanoid robot Nao and a M2M gateway. This demonstrates the soundness of our approach as well as INI's capabilities for constructing context-aware systems. Additionally, since context-aware programs are wide applicable and more complex than regular ones, this poses a higher demand for quality assurance with those kinds of applications. Therefore, we formalize several aspects of INI, including its type system and operational semantics. Furthermore, we develop a tool called INICheck, which can convert a significant subset of INI to Promela, the input modeling language of the model checker SPIN. Hence, SPIN can be applied to verify properties or constraints that need to be satisfied by INI programs. Our tool allows the programmers to have insurance on their code and its behavior.

<p>Current watershed-scale, nonpoint source (NPS) pollution models do not represent the processes and impacts of agricultural best management practices (BMP) on water quality with sufficient detail. To begin addressing this gap, a novel process-based, watershed-scale, water quality model (WEPP-WQ) was developed based on the Water Erosion Prediction Project (WEPP) and the Soil and Water Assessment Tool (SWAT) models. The proposed model was validated at both hillslope and watershed scales for runoff, sediment, and both soluble and particulate forms of nitrogen and phosphorus. WEPP-WQ is now one of only two models which simulates BMP impacts on water quality in ‘high’ detail, and it is the only one not based on USLE sediment predictions. Model validations indicated that particulate nutrient predictions were better than soluble nutrient predictions for both nitrogen and phosphorus. Predictions of uniform conditions outperformed nonuniform conditions, and calibrated model simulations performed better than uncalibrated model simulations. Applications of these kinds of models in real-world, historical simulations are often limited by a lack of field-scale agricultural management inputs. Therefore, a prototype tool was developed to derive management inputs for hydrologic models from remotely sensed imagery at field-scale resolution. At present, only predictions of crop, cover crop, and tillage practice inference are supported and were validated at annual and average annual time intervals based on data availability for the various management endpoints. Extraction model training and validation were substantially limited by relatively small field areas in the observed management dataset. Both of these efforts contribute to computational modeling research and applications pertaining to agricultural systems and their impacts on the environment.</p>