Although there have been oscillations in airship interest since their use in the early 1900s, technological advancements and the need for more flexible and environmentally friendly transportation modes have caused a stream of study and surge in airship development in recent years. For companies and governments to understand how airships can be incorporated into their fleets to fulfil new or existing mission types, system design space exploration is an important step in understanding airships, their uses, and their design parameters. A decision support system (DSS), Design Exploration of Lighter-Than-Air Systems (DELTAS), was developed to help stakeholders with this task. DELTAS allows users to design airships and missions to determine how a design will perform in the scenario. Simulations can also be run for a given mission to find the Pareto-optimal designs for user-defined ranges of high-level airship design parameters. A case study is provided that demonstrates how DELTAS can be used to explore the airship design space for three specified missions. These three mission case studies show how design of experiments is important to more thoroughly cover the design space and to find and understand the relationships between airship design variables that lead to optimal mission times and costs. This research also explores the impacts of introducing an airship into operation. Engineered products have economic, environmental, and social impacts, which comprise the major dimensions of sustainability. This paper seeks to determine the interaction between design parameters when social impacts are incorporated into the concept development phase of the systems design process. Social impact evaluation is increasing in importance similar to what has happened in recent years with environmental impact consideration in the design of engineered products. Concurrently, research into new airship design has increased. Airships have yet to be reintroduced at a large scale or for a range of applications in society. Although airships have the potential for positive environmental and economic impacts, the social impacts are still rarely considered. This paper presents a case study of the hypothetical introduction of airships in the Amazon region of Brazil to help local farmers transport their produce to market. It explores the design space in terms of both engineering parameters and social impacts using a discrete-event simulation to model the system. The social impacts are found to be dependent not only on the social factors and airship design parameters, but also on the farmer-airship system, suggesting that socio-technical systems design will benefit from integrated social impact metric analysis. This thesis seeks to demonstrate how computer-aided engineering tools can be used to predict social impacts, to more effectively explore a system's design space, and to optimize the system design for maximum positive impact, using the modern airship as a case study.

High Level Synthesis (HLS) is a methodology to translate a model developed in a high abstraction layer, e.g. C/C++/SystemC, that describes the algorithm into a Register-Transfer level (RTL) description like Verilog or VHDL. The resulting RTL description from the translation is subject to multiple user-controlled directives and an internal design space exploration algorithm specific to the toolchain used. HLS allow designers to focus on the behaviour of the design at a higher abstraction compared to the behavioural modelling available within the Hardware Description Language (HDL) as the compiler decides the movement of data and timing in the resulting design. Ericsson uses a legacy Advanced Peripheral Bus (APB) like interface called Memory/Register Interface (MIRI) interface for data movement in a subsystem of one of their Application-Specific Integrated Circuit (ASIC). The thesis attempts to upgrade the protocol to the more performant ARM Advanced Microcontroller Bus Architecture (AMBA) protocols’ Advanced High-performance Bus (AHB) or Advanced eXtensible Interface (AXI) interfaces. SystemC provides a host of functionalities to define the complete behaviour of the circuit at a high level of abstraction. This thesis will explore the effect of the structuring SystemC models on their synthesis, and perform design space exploration to understand the best design methodology to adopt in a SystemC model design and compare the models based on the final synthesis metrics like area, timing, and register counts. The toolchain for the thesis will be the Stratus HLS compiler developed by Cadence. Stratus supports all synthesizable constructs of SystemC. Most HLS research focuses on improving Design Space Exploration algorithms used internally in the HLS tools. However, designers can utilize algorithm structuring to provide the HLS engines with a better starting point. In this thesis, the Stratus toolchain will be used to experiment with different models with equivalent behaviour and performance. Thereafter, extract which constructs used in the models are optimal for allowing the internal design space exploration algorithm to perform in the best way possible. / HLS är en metod för att översätta en modell utvecklad på hög abstraktionsnivå t.ex. C/C++/SystemC som beskriver algoritmen på registeröverföringsnivå (RTL) som Verilog eller VHDL. Den resulterande RTL-beskrivningen utsätts för flera användarkontrollerade direktiv och en intern Design Space Exploration (DSE) algoritm, vilken är specifik för den verktygskedja som används. Detta gör det möjligt för en designer att fokusera på konstruktion beteende på en högre abstraktionsnivå jämfört med den beteendemodellering som finns tillgänglig inom det hårdvarubeskrivande språket (HDL:en) när kompilatorn bestämmer tidpunkten för utbytet av data i den resulterande designen. Ericsson använder ett äldre gränssnitt för Advanced Peripheral Bus (APB) som kallas Memory/Register Interface (MIRI), vilket är ett gränssnitt för utbyte av data i ett delsystem i en av deras Application-Specific Integrated Circuit (ASIC:ar). Avhandlingen försöker uppgradera protokollet till ett av de det mer högpresterande ARM Advanced Microcontroller Bus Architecture – protokollen Advanced High-Performance Bus (AHB) eller Advanced eXtensible Interface (AXI). SystemC tillhandahåller en mängd funktioner för att definiera kretsens fullständiga beteende vid en hög abstraktionsnivå. Denna avhandling utforskar effekten av strukturerade SystemC-modeller och deras syntesresultat samt konstruktionsrymden, för att förstå den bästa designmetodiken i ett SystemC-modelleringsdesignflöde och jämföra modellerna baserade på de slutliga syntesmätvärdena som storlek, timing, etc. Verktygskedjan för avhandlingen kommer att vara Stratus HLS -kompilatorn som utvecklats av Cadence. Stratus stöder alla syntetiserbara konstruktioner av SystemC. HLS-forskningen fokuserar främst på att förbättra Design Space Exploration, dvs de algoritmer som används internt i HLS-verktygen för att komma fram till lösningar. För att ge HLS -motorerna en bättre utgångspunkt. I denna avhandling kommer Stratus att användas för att utvärdera olika modeller med ekvivalent beteende och nästan samma prestanda efter Syntes, för att komma fram till vilka konstruktioner är optimala för att den interna DSE-algoritmen skall fungera bäst.

The increasing demand for energy efficient computing has endorsed the usage of Field-Programmable Gate Arrays to create hardware accelerators for large and complex codes. However, implementing such accelerators involve two complex decisions. The first one lies in deciding which code snippet is the best to create an accelerator, and the second one lies in how to implement the accelerator. When considering both decisions concomitantly, the problem becomes more complicated since the code snippet implementation affects the code snippet choice, creating a combined design space to be explored. As such, a fast design space exploration for the accelerators implementation is crucial to allow the exploration of different code snippets. However, such design space exploration suffers from several time-consuming tasks during the compilation and evaluation steps, making it not a viable option to the snippets exploration. In this work, we focus on the efficient implementation of pipelined hardware accelerators and present our contributions on speeding up the pipelines creation and their design space exploration. Towards loop pipelining, the proposed approaches achieve up to 100× speed-up when compared to the state-uf-the-art methods, leading to 164 hours saving in a full design space exploration with less than 1% impact in the final results quality. Towards design space exploration, the proposed methods achieve up to 9:5× speed-up, keeping less than 1% impact in the results quality. / A demanda crescente por computação energeticamente eficiente tem endossado o uso de Field- Programmable Gate Arrays para a criação de aceleradores de hardware para códigos grandes e complexos. Entretanto, a implementação de tais aceleradores envolve duas decisões complexas. O primeiro reside em decidir qual trecho de código é o melhor para se criar o acelerador, e o segundo reside em como implementar tal acelerador. Quando ambas decisões são consideradas concomitantemente, o problema se torna ainda mais complicado dado que a implementação do trecho de código afeta a seleção dos trechos de código, criando um espaço de projeto combinatorial a ser explorado. Dessa forma, uma exploração do espaço de projeto rápida para a implementação de aceleradores é crucial para habilitar a exploração de diferentes trechos de código. Contudo, tal exploração do espaço de projeto é impedida por várias tarefas que consumem tempo durante os passos de compilação a análise, o que faz da exploração de trechos de códigos inviável. Neste trabalho, focamos na implementação eficiente de aceleradores pipeline em hardware e apresentamos nossas contribuições para o aceleramento da criações de pipelines e de sua exploração do espaço de projeto. Referente à criação de pipelines, as abordagens propostas alcançam uma aceleração de até 100× quando comparadas às abordagens do estado-da-arte, levando à economia de 164 horas em uma exploração de espaço de projeto completa com menos de 1% de impacto na qualidade dos resultados. Referente à exploração do espaço de projeto, as abordagens propostas alcançam uma aceleração de até 9:5×, mantendo menos de 1% de impacto na qualidade dos resultados.

Devido ao grande número de otimizações fornecidas pelos compiladores modernos e à ampla possibilidade de ordenação dessas transformações, uma eficiente Exploração do Espaço de Projeto (DSE) se faz necessária para procurar a melhor sequência de otimização de uma determinada função ou fragmento de código. Como esta exploração é uma tarefa complexa e dispendiosa, apresentamos uma nova abordagem de DSE capaz de reduzir esse tempo de exploração e selecionar sequências de otimização que melhoraram o desempenho dos códigos transformados. Nossa abordagem utiliza um conjunto de funções de referência, para as quais uma representação simbólica do código (DNA) e a melhor sequência de otimização são conhecidas. O DSE de novas funções é baseado em uma abordagem de agrupamento aplicado sobre o código DNA que identifica similaridades entre funções. O agrupamento utiliza três técnicas para a mineração de dados: distância de compressão normalizada, algoritmo de reconstrução de árvores filogenéticas (Neighbor Joining) e identificação de grupos por ambiguidade. As otimizações das funções de referência identificadas como similares formam o espaço que é explorado para encontrar a melhor sequência para a nova função. O DSE pode utilizar o conjunto reduzido de otimizações de duas formas: como o espaço de projeto ou como a configuração inicial do algoritmo. Em ambos os casos, a adoção de uma pré-seleção baseada no agrupamento permite o uso de algoritmos de busca simples e rápidos. Os resultados experimentais revelam que a nova abordagem resulta numa redução significativa no tempo total de exploração, ao mesmo tempo que alcança um desempenho próximo ao obtido através de uma busca mais extensa e dispendiosa baseada em algoritmos genéticos. / Due to the large number of optimizations provided in modern compilers and to compiler optimization specific opportunities, a Design Space Exploration (DSE) is necessary to search for the best sequence of compiler optimizations for a given code fragment (e.g., function). As this exploration is a complex and time consuming task, we present new DSE strategies to reduce the exploration time and still select optimization sequences able to improve the performance of each function. The DSE is based on a clustering approach which groups functions with similarities and then explore the reduced search space provided by the optimizations previously suggested for the functions in each group. The identification of similarities between functions uses a data mining method which is applied to a symbolic representation of the source code. The DSE strategies uses the reduced optimizations set identified by clustering in two ways: as the design space or as the initial configuration of the algorithm. In both ways, the adoption of a pre-selection based on clustering allows the use of simple and fast DSE algorithms. Several experiments for evaluating the effectiveness of the proposed approach address the exploration of compiler optimization sequences. Besides, we investigate the impact of each technique or component employed in the selection process. Experimental results reveal that the use of our new clustering-based DSE approach achieved a significant reduction on the total exploration time of the search space at the same time that obtained performance speedups close to a traditional genetic algorithmbased approach.

Este trabalho propõe uma nova abordagem para o desenvolvimento de sistemas embarcados, através da combinação da abstração e propriedades de verificação de modelos da linguagem declarativa Alloy com a ampla aceitação de Java na indústria. A abordagem surge no contexto de que a automação de software no domínio embarcado tornou-se extremamente necessária, uma vez que atualmente a maior parte do tempo de desenvolvimento é gasta no projeto de software de produtos tão restritos em termos de recursos. As ferramentas de automação de software embarcado devem atender a demanda por produtividade e manutenibilidade, mas respeitar restrições naturais deste tipo de sistema, tais como espaço de memória, potência e desempenho. As ferramentas de automação de projeto lidam com produtividade e manutenibilidade ao permitir especificações de alto nível, tarefa difícil de atender no domínio embarcado devido ao comportamento misto de muitas aplicações embarcadas. Abordagens que promovem meios para verificação formal também são atrativas, embora geralmente sejam difíceis de usar, e por este motivo não são de grande auxílio na tarefa de reduzir o tempo de chegada ao mercado do produto. Através do uso de Alloy, baseada em lógica de primeira-ordem, é possível obter especificações em altonível e verificação formal de modelos com uma única linguagem. Este trabalho apresenta a poderosa abstração proporcionada pela linguagem Alloy em aplicações embarcadas, assim como regras para obter automaticamente código Java a partir de modelos Alloy. A geração de código Java a partir de modelos Alloy, combinada a uma ferramenta de estimativa, provê exploração de espaço de projeto, atendendo assim as fortes restrições do projeto de software embarcado, o que normalmente não é contemplado pela engenharia de software tradicional. / This work proposes a new approach for embedded software development, by combining the abstraction and model verification properties of the Alloy declarative language with the broad acceptance in industry of Java. The approach comes into play since software automation in the embedded domain has become a major need, as currently most of the development time is spent designing software for such hardconstrained resources products. Design automation tools for embedded systems must meet the demand for productivity and maintainability, but constraints such as memory, power and performance must still be considered. Design automation tools deal with productivity and maintainability by allowing high-level specifications, which is hard to accomplish on the embedded domain due to the mixed behavior nature of many embedded applications. Approaches that provide means for formal verification are also attractive, but their usage is usually not straightforward, and for this reason they are not that helpful in dealing with time-tomarket constraints. By using Alloy, based in first-order logic, it is possible to obtain high-level specifications and formal model verification with a single language. This work shows the powerful abstraction provided by the Alloy language for embedded applications, as well as rules for obtaining automatically Java code from Alloy models. The Java source code generation from Alloy models, combined with an estimation tool, provides design space exploration to match tight embedded software design constraints, what is usually not taken into account by standard software engineering techniques.

Dans le cadre de la synthèse de haut niveau (SHN), qui permet d'extraire un modèle structural à partir d'un modèle algorithmique, nous proposons des solutions pour opti- miser l'accès et le transfert de données du matériel cible. Une méthodologie d'exploration de l'espace des architectures mémoire possibles a été mise au point. Cette méthodologie trouve un compromis entre la quantité de mémoire interne utilisée et les performances temporelles du matériel généré. Deux niveau d'optimisation existe : 1. Une optimisation architecturale, qui consiste à créer une hiérarchie mémoire, 2. Une optimisation algorithmique, qui consiste à partitionner la totalité des données manipulées pour stocker en interne seulement celles qui sont utiles dans l'immédiat. Pour chaque répartition possible, nous résolvons le problème de l'ordonnancement des calculs et de mapping des données. À la fin, nous choisissons la ou les solutions pareto. Nous proposons un outil, front-end de la SHN, qui est capable d'appliquer l'optimisation algorithmique du point 2 à un algorithme de traitement d'image spécifié par l'utilisateur. L'outil produit en sortie un modèle algorithmique optimisé pour la SHN, en customisant une architecture générique.

In the design of a multi-processor System-on-a-Chip (SoC), the bus architecture typically comes to the forefront because the system performance is not dependent only on the speed of the Processing Elements (PEs) but also on the bus architecture in the system. An efficient bus architecture with effective arbitration for reducing contention on the bus plays an important role in maximizing performance. Therefore, among many issues of multi-processor SoC research, we focus on two issues related to the bus architecture in this dissertation. One issue is how to quickly and easily design an efficient bus architecture for an SoC. The second issue is how to quickly explore the design space across performance influencing factors to achieve a high performance bus system. The objective of this research is to provide a Computer-Aided Design (CAD) tool with which the user can quickly explore System-on-a-Chip (SoC) bus design space in search of a high performance SoC bus system. From a straightforward description of the numbers and types of Processing Elements (PEs), non-PEs, memories and buses (including, for example, the address and data bus widths of the buses and memories), our Bus Synthesis tool, called BusSynth, generates a Register-Transfer Level (RTL) Verilog Hardware Description Language (HDL) description of the specified bus system. The user can utilize this RTL Verilog in bus-accurate simulations to more quickly arrive at an efficient bus architecture for a multi-processor SoC. The methodology we propose gives designers a great benefit in fast design space exploration of bus systems across a variety of performance influencing factors such as bus types, PE types and software programming styles (e.g., pipelined parallel fashion or functional parallel fashion). We also show that BusSynth can efficiently generate bus systems in a matter of seconds as opposed to weeks of design effort to integrate together each system component by hand. Moreover, unlike the previous related work, BusSynth can support a wide variety of PEs, memory types and bus architectures (including a hybrid bus architecture) in search of a high performance SoC.

Recent years have witnessed the emergence of microprocessors that are embedded within a plethora of devices used in everyday life. Embedded architectures are customized through a meticulous and time consuming design process to satisfy stringent constraints with respect to performance, area, power, and cost. In embedded systems, the cost of the memory hierarchy limits its ability to play as central a role. This is due to stringent constraints that fundamentally limit the physical size and complexity of the memory system. Ultimately, application developers and system engineers are charged with the heavy burden of reducing the memory requirements of an application. This thesis offers the intriguing possibility that compilers can play a significant role in the automatic design space exploration and optimization of embedded memory systems. This insight is founded upon a new analytical model and novel compiler optimizations that are specifically designed to increase the synergy between the processor and the memory system. The analytical models serve to characterize intrinsic program properties, quantify the impact of compiler optimizations on the memory systems, and provide deep insight into the trade-offs that affect memory system design.

Bildverarbeitungsanwendungen stellen besondere Ansprüche an das ausführende Rechensystem. Einerseits ist eine hohe Rechenleistung erforderlich. Andererseits ist eine hohe Flexibilität von Vorteil, da die Entwicklung tendentiell ein experimenteller und interaktiver Prozess ist. Für neue Anwendungen tendieren Entwickler dazu, eine Rechenarchitektur zu wählen, die sie gut kennen, anstatt eine Architektur einzusetzen, die am besten zur Anwendung passt. Bildverarbeitungsalgorithmen sind inhärent parallel, doch herkömmliche bildverarbeitende eingebettete Systeme basieren meist auf sequentiell arbeitenden Prozessoren. Im Gegensatz zu dieser "Unstimmigkeit" können hocheffiziente Systeme aus einer gezielten Synergie aus Software- und Hardwarekomponenten aufgebaut werden. Die Konstruktion solcher System ist jedoch komplex und viele Lösungen, wie zum Beispiel grobgranulare Architekturen oder anwendungsspezifische Programmiersprachen, sind oft zu akademisch für einen Einsatz in der Wirtschaft. Die vorliegende Arbeit soll ein Beitrag dazu leisten, die Komplexität von Hardware-Software-Systemen zu reduzieren und damit die Entwicklung hochperformanter on-Chip-Systeme im Bereich Bildverarbeitung zu vereinfachen und wirtschaftlicher zu machen. Dabei wurde Wert darauf gelegt, den Aufwand für Einarbeitung, Entwicklung als auch Erweiterungen gering zu halten. Es wurde ein Entwurfsfluss konzipiert und umgesetzt, welcher es dem Softwareentwickler ermöglicht, Berechnungen durch Hardwarekomponenten zu beschleunigen und das zu Grunde liegende eingebettete System komplett zu prototypisieren. Hierbei werden komplexe Bildverarbeitungsanwendungen betrachtet, welche ein Betriebssystem erfordern, wie zum Beispiel verteilte Kamerasensornetzwerke. Die eingesetzte Software basiert auf Linux und der Bildverarbeitungsbibliothek OpenCV. Die Verteilung der Berechnungen auf Software- und Hardwarekomponenten und die daraus resultierende Ablaufplanung und Generierung der Rechenarchitektur erfolgt automatisch. Mittels einer auf der Antwortmengenprogrammierung basierten Entwurfsraumexploration ergeben sich Vorteile bei der Modellierung und Erweiterung. Die Systemsoftware wird mit OpenEmbedded/Bitbake synthetisiert und die erzeugten on-Chip-Architekturen auf FPGAs realisiert. / Image processing applications have special requirements to the executing computational system. On the one hand a high computational power is necessary. On the other hand a high flexibility is an advantage because the development tends to be an experimental and interactive process. For new applications the developer tend to choose a computational architecture which they know well instead of using that one which fits best to the application. Image processing algorithms are inherently parallel while common image processing systems are mostly based on sequentially operating processors. In contrast to this "mismatch", highly efficient systems can be setup of a directed synergy of software and hardware components. However, the construction of such systems is complex and lots of solutions, like gross-grained architectures or application specific programming languages, are often too academic for the usage in commerce. The present work should contribute to reduce the complexity of hardware-software-systems and thus increase the economy of and simplify the development of high-performance on-chip systems in the domain of image processing. In doing so, a value was set on keeping the effort low on making familiar to the topic, on development and also extensions. A design flow was developed and implemented which allows the software developer to accelerate calculations with hardware components and to prototype the whole embedded system. Here complex image processing systems, like distributed camera sensor networks, are examined which need an operating system. The used software is based upon Linux and the image processing library OpenCV. The distribution of the calculations to software and hardware components and the resulting scheduling and generation of architectures is done automatically. The design space exploration is based on answer set programming which involves advantages for modelling in terms of simplicity and extensions. The software is synthesized with the help of OpenEmbedded/Bitbake and the generated on-chip architectures are implemented on FPGAs.

Unmanned Aerial Vehicles (UAVs) are the most dynamic growth sector of the aerospace industry today. The need to provide persistent intelligence, surveillance, and reconnaissance for military operations is driving the planned acquisition of over 5,000 UAVs over the next five years. The most pressing need is for quiet, small UAVs with endurance beyond what is capable with advanced batteries or small internal combustion propulsion systems. Fuel cell systems demonstrate high efficiency, high specific energy, low noise, low temperature operation, modularity, and rapid refuelability making them a promising enabler of the small, quiet, and persistent UAVs that military planners are seeking. Despite the perceived benefits, the actual near-term performance of fuel cell powered UAVs is unknown. Until the auto industry began spending billions of dollars in research, fuel cell systems were too heavy for useful flight applications. However, the last decade has seen rapid development with fuel cell gravimetric and volumetric power density nearly doubling every 2-3 years. As a result, a few design studies and demonstrator aircraft have appeared, but overall the design methodology and vehicles are still in their infancy. The design of fuel cell aircraft poses many challenges. Fuel cells differ fundamentally from combustion based propulsion in how they generate power and interact with other aircraft subsystems. As a result, traditional multidisciplinary analysis (MDA) codes are inappropriate. Building new MDAs is difficult since fuel cells are rapidly changing in design, and various competitive architectures exist for balance of plant, hydrogen storage, and all electric aircraft subsystems. In addition, fuel cell design and performance data is closely protected which makes validation difficult and uncertainty significant. Finally, low specific power and high volumes compared to traditional combustion based propulsion result in more highly constrained design spaces that are problematic for design space exploration. To begin addressing the current gaps in fuel cell aircraft development, a methodology has been developed to explore and characterize the near-term performance of fuel cell powered UAVs. The first step of the methodology is the development of a valid MDA. This is accomplished by using propagated uncertainty estimates to guide the decomposition of a MDA into key contributing analyses (CAs) that can be individually refined and validated to increase the overall accuracy of the MDA. To assist in MDA development, a flexible framework for simultaneously solving the CAs is specified. This enables the MDA to be easily adapted to changes in technology and the changes in data that occur throughout a design process. Various CAs that model a polymer electrolyte membrane fuel cell (PEMFC) UAV are developed, validated, and shown to be in agreement with hardware-in-the-loop simulations of a fully developed fuel cell propulsion system. After creating a valid MDA, the final step of the methodology is the synthesis of the MDA with an uncertainty propagation analysis, an optimization routine, and a chance constrained problem formulation. This synthesis allows an efficient calculation of the probabilistic constraint boundaries and Pareto frontiers that will govern the design space and influence design decisions relating to optimization and uncertainty mitigation. A key element of the methodology is uncertainty propagation. The methodology uses Systems Sensitivity Analysis (SSA) to estimate the uncertainty of key performance metrics due to uncertainties in design variables and uncertainties in the accuracy of the CAs. A summary of SSA is provided and key rules for properly decomposing a MDA for use with SSA are provided. Verification of SSA uncertainty estimates via Monte Carlo simulations is provided for both an example problem as well as a detailed MDA of a fuel cell UAV. Implementation of the methodology was performed on a small fuel cell UAV designed to carry a 2.2 kg payload with 24 hours of endurance. Uncertainty distributions for both design variables and the CAs were estimated based on experimental results and were found to dominate the design space. To reduce uncertainty and test the flexibility of the MDA framework, CAs were replaced with either empirical, or semi-empirical relationships during the optimization process. The final design was validated via a hardware-in-the loop simulation. Finally, the fuel cell UAV probabilistic design space was studied. A graphical representation of the design space was generated and the optima due to deterministic and probabilistic constraints were identified. The methodology was used to identify Pareto frontiers of the design space which were shown on contour plots of the design space. Unanticipated discontinuities of the Pareto fronts were observed as different constraints became active providing useful information on which to base design and development decisions.