No description available.

The goal of this thesis is to design a user interface and to implement an application that is used for test execution in test management tool TestLink. This application is designed to streamline and simplify the process of test execution in this tool. The theoretical part of the thesis describes features and the interface of TestLink and compares it with other similar tools. The practical part is focused on analysis, user interface design, and implementation of the application. The outcome of this thesis is in addition to the application itself also a library written in PHP, which is used for communication with the application programming interface of TestLink and which simplifies the creation of similar applications.

<p>The commercial CubeSat industry has experienced explosive growth recently, and with falling  costs  and  growing  numbers  of  launch  providers,  the  trend  is  likely  to  continue.  The scientific missions CubeSats could complete are expanding, and this has resulted in a demand for reliable  high  specific  impulse  nanosatellite  propulsion  systems.  Interest  in  liquid-fed  pulsed plasma thrusters (LF-PPTs) to fulfill this role has grown lately. Prior work on a nanosatellite LF-PPT was done in the Purdue Electric Propulsion and Plasma Laboratory, but its high operational voltage and electrode size would be disadvantageous for integration on a CubeSat, which have strict volume limitations and provide only tens of Watts in power at low voltages. This work aims to address those disadvantages and further advance the development of a nanosatellite LF-PPT by reducing the operating voltage and removing long plate electrodes to prevent energy losses on components other than the expelled plasma sheet. Two major objectives are pursued: to construct a  coaxial  pulsed  plasma  thruster  operating  with  10s  to  100s  of  volts  and  to  characterize  the temporal evolution of the discharge parameters in this low-voltage operation scenario. </p> <p>It  took  three  experimental  design  iterations,  all  of  which  used  a  260  <em>uF</em> ,  400 <em>V</em> film capacitor, to arrive at a functional coaxial pulsed plasma thruster. First, a button gun was tested. It produced  a  peak  current  of ~16<em> kA</em>,  which  serves  as  the  expected  maximum  for  the  later experiments. Due to the presence of parasitic arcing, it revealed that electrical lines needed to be removed from vacuum chamber to enable testing at a wide range of pressures. Second, a coaxial PPT was designed, built, and tested. This design confirmed operation at discharge voltages <100 <em>V</em> across the plasma, achieving one of the project’s aims, and produced a peak current of 7.4 <em>kA</em>. However,  necessity  to  better  align  the  cathode and  provide  an  unobstructed  camera  view  for observation of the discharge column attachment to the cathode surface forced additional system redesign. Third, a revised coaxial PPT was built and tested. Using air as a propellant, the discharge generated a peak current of 10.4 <em>kA</em> at a mass flow rate of 2 mgs. The PPT cathode was imaged with an ICCD camera over a wide range of pressures, and the photos indicated “spotless” diffuse arc attachment to the cathode, which serves as evidence to expect low erosion rates. The direct measurements of the cathode erosion rate are planned for future. </p>

Can the Product Development Process at Tcom be improved by moving usability testing in-house? The interest in this question lies in the agile transformation Tcom initiated in early 2018. Once agile, the company’s interests are efficiency and increasing quality. One way of increasing the quality of their digital products is to improve the process behind it, where involving users in usability testing should be central in an iterative development process. A qualitatively driven mixed methods research approach facilitated the acquisition of the empirical data necessary to successfully answer the research question. The culture of Tcom’s usability testing was collected via a survey. The survey was complemented with the current testing process through four interviews and two observations of usability tests, one internal and one external. Parameters between the two tests were compared and weighted against each other. The main findings reveal that the internal process shows promising characteristics. It is, up to, 1/10 as expensive per participant, has a quicker call-to-test-time, facilitates transparency, and allows refinement of the process. With the main findings in hand, the conclusion points to the fact that usability testing should be composed and conducted by Tcom itself. The greatest challenge to such a change is how a usability perspective can be integrated into the Scrum methodology. / Kan produktutvecklingsprocessen på Tcom förbättras genom att flytta användbarhetstester internt? Intresset i denna fråga ligger i den agila transformation som företaget påbörjade tidigt 2018. Effektivitet och kvalitet är centrala förbättringspunkter med det agila arbetssättet. Ett sätt att öka kvaliteten på deras digitala produkter är att förbättra processen bakom, där involveringen av användare i användbarhetstester bör vara centralt i ett iterativt arbetsförlopp. En kvalitativt driven mixed methods research metod tillämpades för att förvärva den empiriska data som krävdes för att framgångsrikt besvara frågeställningen. Tcoms användbarhetstestkultur undersöktes via en enkät. Denna metod kompletterades med 4 intervjuer och 2 observationer av användbarhetstest, ett externt och ett internt. Parametrar från de två observationerna ställdes mot varandra. De centrala upptäckterna avslöjar att den interna processen uppvisar lovande egenskaper. Den är upp till en tiondel så kostsam per deltagare, har snabbare beställning-till-test-tid, tillåter transparens, och möjliggör förbättring av själva testprocessen. Med hänsyn till huvudfynden kan vi konkludera att användbarhetstest bör utformas och utföras av Tcom själva. Den största utmaningen till en sådan förändring ligger i hur ett sådant användbarhetsperspektiv ska implementeras i det agila ramverket Scrum.

<p>Activity planning for space mission operations has traditionally been a human-in-the-loop effort, conducted by ground operators. Over the past two decades, advances have been made toward automating the mission planning process, in an effort to improve the efficiency of the mission operations system, while increasing the mission return. In keeping with NASA’s goals, some aspects of onboard mission planning are increasingly used for complex missions, particularly for planetary surface missions that are subject to long communication delays.</p> <p>This dissertation research develops an automated mission planning framework and applies it to two spacecraft scenario case studies: a science orbiter and a science rover mission. Mission plans are optimized on the basis of science return, accommodating spacecraft movement</p> <p>to sites of scientific interest according to ground-team preferences, while staying within rover engineering and traverse-related constraints. Automated mission planners offer the capability to schedule engineering and science activities onboard, without ground-in-the-loop interaction. Resource modeling and path planning can be done onboard, reducing the need for modeling and verification by ground operators. Further, automated mission planners</p> <p>may incorporate an optimization executive that maximizes the mission return within the available resource constraints. The proposed planners may be utilized onboard autonomous spacecraft and rovers with limited human support. Also, they may be run on the ground by</p> <p>mission planning teams to provide additional insight during the planning process. Utilizing a variety of optimization approaches, the developed automated mission planners establish the planned sequence of activities, including and engineering activities, while adhering to constraints imposed by orbital geometry or planetary pathing requirements and resource availability. The focus of the work is on remote, robotic missions in which human-in-the loop decision input is delayed or at times unavailable. Two major classes of robotic missions are examined: Orbital science missions in which primary science activities are performed periodically at a specified rate, and a planetary rover mission in which a larger variety of science activities are interspersed with unique terrain navigation activities. The automated mission planning framework is designed to be adapted based upon the application. Optimization methods suitable for different mission planning problems are presented, comparing methods on the basis of computation speed, resources required and solution value.</p> <p>The Aerospace Systems Engineering definitions for “robustness” and “flexibility” are given quantifiable, mathematical definitions and are incorporated into the framework as quality metrics to provide criteria with which to evaluate and compare the produced activity plans.</p> <p>The metrics “reliability” and “latent performance index” provide additional criteria for plan evaluation. A variety of automated mission planning algorithmic approaches are developed and described functionally and mathematically. Planning tools capable of plan verification, Monte Carlo simulation-based verification and plan variation analysis are developed and described in detail. Two detailed, step by step case studies are developed, applying and</p> <p>running all the mission planning and analysis tools to provide planning solutions and analysis of generated plans for the science orbiter and science rover scenarios. The application of the developed planning solutions to the presented missions, including the determination</p> <p>of the quality metrics, are seen as the primary contributions to the advancement of the</p> <p>state of the art in automated mission planning. The Automated Mission Planning and plan analysis techniques and practices are summarized into a User’s Guide to Automated Mission Planning. The guide aids the user in developing their own automated mission planning framework and applying it to their unique mission planning problems. Numerous avenues for future work are proposed to extend this research into other, useful areas. Two areas of road mapping—tasks that must be done to enable a future vision for improved automated planning—are discussed.</p>

This study examined the relationship between attitudes and aptitudes toward Computer-aided design (CAD) and personality types among interior design students. Twenty-eight junior and 28 senior interior design students at Virginia Polytechnic Institute and State University comprised the population of this study. Information was mainly obtained from the survey questionnaire and Keirsey Temperament Sorter which were administered during the last week of the spring semester 1991. The collected data was analyzed by descriptive statistics. The frequency distribution and mean scores were used to describe the characteristics of the sample population, attitudes and aptitudes toward CAD, and personality types. Correlation coefficients were used to examine the hypotheses of this study that a significant relationship exists between students' attitudes and aptitudes toward CAD and personality types. Results of this study revealed that students seem to have higher preference for Extravert, Intuition, Feeling, and Judging types rather than Introvert, Sensing, Thinking, and Perceiving. This finding suggests that most students in the classes tended to perceive things by intuition, relied more on empathy and sensitivity in making judgment, and made systematic, orderly judgements about the world. It was found that the students who had stronger attitudes toward CAD usefulness tended to be the Feeling type rather than Thinking. It was also discovered that there was a correlation between the Judging type and higher CAD proficiency grades. While only an isolated case, this study revealed a significant difference between the CAD instructor and stUdents in personality types.the world. It was found that the students who had stronger attitudes toward CAD usefulness tended to be the Feeling type rather than Thinking. It was also discovered that there was a correlation between the Judging type and higher CAD proficiency grades. While only an isolated case, this study revealed a significant difference between the CAD instructor and students in personality types. / Master of Science

<p dir="ltr">At the cusp of scientific discovery and innovation, mankind's next greatest challenge lies in developing capabilities to enable human presence in deep space. This entails setting up space infrastructure, travel pathways, managing spacecraft traffic, and building up deep space operation logistics. Spacecrafts that are a part of the infrastructure must be able to perform myriad of operations and transfers such as rendezvous and docking, station-keeping, loitering, collision avoidance etc. In support of this endeavour, an investigation is done to analyze and recreate the solution space for fuel-optimal trajectories and control histories required for onboard trajectory design of inexpensive spacecraft transfers and operations. This study investigates close range rendezvous (CRR), nearby orbital transfer, collision avoidance, and long range transfer maneuvers for spacecrafts whose highly complex and nonlinear behavior is modelled using the circular restricted three-body problem (CR3BP) dynamics and to which a finite-burn maneuver is augmented to model low-propulsion maneuvers. In order to study the nonlinear solution space for such maneuvers, this investigation contributes new formulations of nonlinear programming (NLP) optimal control problems solved to minimize fuel consumption, and validated by traditional methods already in use. This investigation proposes a Feature Learning based Optimal Control Method (L-OCM) to learn the solution space and recreate results in real-time. The NLP problem is solved off-line for a range of initial conditions. The set of solutions is used to generate datasets with initial conditions as inputs and the identified features of the optimal control solution as outputs. These features are inherent to reconstructing the optimal control histories of the solution and are selected keeping onboard computational capabilities in mind. Deep Neural Networks (DNNs) are trained to map the complex, nonlinear relationship between the inputs and outputs, and then implemented to find on-line solutions to any initial condition. The L-OCM method provides fuel-optimal, real-time solutions that can be implemented by a spacecraft performing operations in cislunar space.</p>

<p dir="ltr">This thesis presents a comprehensive exploration of advanced optimization strategies for addressing mixed-integer optimal control problems (MIOCPs) in aerospace applications, emphasizing the enhancement of convergence robustness, computational efficiency, and accuracy. The research develops a broad spectrum of optimization methodologies, including multi-phase approaches, parallel computing, reinforcement learning (RL), and distributed algorithms, to tackle complex MIOCPs characterized by highly nonlinear dynamics, intricate constraints, and discrete control variables.</p><p dir="ltr">Through discretization and reformulation, MIOCPs are transformed into general quadratically constrained quadratic programming (QCQP) problems, which are then equivalently converted into rank-one constrained semidefinite programs problems. To address these, iterative algorithms are developed specifically for solving such problems. Initially, two iterative search methods are introduced to achieve convergence: one is a hybrid alternating direction method of multipliers (ADMM) designed for large-scale QCQP problems, and the other is an iterative second-order cone programming (SOCP) algorithm developed to achieve global convergence. Moreover, to facilitate the convergence of these iterative algorithms and to enhance their solution quality, a multi-phase strategy is proposed. This strategy integrates with both the iterative ADMM and SOCP algorithms to optimize the solving of QCQP problems, improving both the convergence rate and the optimality of the solutions. To validate the effectiveness and improved computational performance of the proposed multi-phase iterative algorithms, the proposed algorithms were applied to several aerospace optimization problems, including six-degree-of-freedom (6-DoF) entry trajectory optimization, fuel-optimal powered descent, and multi-point precision landing challenges in a human-Mars mission. Theoretical analyses of convergence properties along with simulation results have been conducted, demonstrating the efficiency, robustness, and enhanced convergence rate of the optimization framework.</p><p dir="ltr">However, the iteration based multi-phase algorithms primarily guarantee only local optima for QCQP problems. This research introduces a novel approach that integrates a distributed framework with stochastic search techniques to overcome this limitation. By leveraging multiple initial guesses for collaborative communication among computation nodes, this method not only accelerates convergence but also enhances the exploration of the solution space in QCQP problems. Additionally, this strategy extends to tackle general nonlinear programming (NLP) problems, effectively steering optimization toward more globally promising directions. Numerical simulations and theoretical proofs validate these improvements, marking significant advancements in solving complex optimization challenges.</p><p dir="ltr">Following the use of multiple agents in QCQP problems, this research expand this advantage to address more general rank-constrained semidefinite programs (RCSPs). This research developed a method that decomposes matrices into smaller submatrices for parallel processing by multiple agents within a distributed framework. This approach significantly enhances computational efficiency and has been validated in applications such as image denoising, showcasing substantial improvements in both efficiency and effectiveness.</p><p dir="ltr">Moreover, to address uncertainties in applications, a learning-based algorithm for QCQPs with dynamic parameters is developed. This method creates high-performing initial guesses to enhance iterative algorithms, specifically applied to the iterative rank minimization (IRM) algorithm. Empirical evaluations show that the RL-guided IRM algorithm outperforms the original, delivering faster convergence and improved optimality, effectively managing the challenges of dynamic parameters.</p><p dir="ltr">In summary, this thesis introduces advanced optimization strategies that significantly enhance the resolution of MIOCPs and extends these methodologies to more general issues like NLP and RCSP. By integrating multi-phase approaches, parallel computing, distributed techniques, and learning methods, it improves computational efficiency, convergence, and solution quality. The effectiveness of these methods has been empirically validated and theoretically confirmed, representing substantial progress in the field of optimization.</p>

<div>In order to answer the most pressing scientific questions about the two Martian moons, Phobos and Deimos, new remote sensing observations are required. The best way to obtain global high resolution observations of Phobos and Deimos is through dedicated missions to each body that utilize close-proximity orbits, however much of the orbital tradespace is too unstable to realistically or safely operate a mission.</div><div><br></div><div>This thesis explores the dynamics and stability characteristics of trajectories near Deimos. The family of distant retrograde orbits that are inclined out of the Deimos equatorial plane, known as quasi-satellite orbits, are explored extensively. To inform future mission design and CONOPS, the sensitivities and stability of distant retrograde and quasi-satellite orbits are examined in the vicinity of Deimos, and strategies for transferring between DROs are demonstrated. Finally, a method for designing quasi-satellite science orbits is demonstrated for a set of notional instruments and science requirements for a Deimos remote sensing mission.<br></div>

<p>  </p> <p>High altitude test facilities are needed for ground testing of upper stage rocket engines or small satellite thrusters with high expansion ratio nozzles to ensure full-flowing nozzle conditions. Rocket exhaust diffusers and ejector systems are essential components of these facilities and are frequently used to set desired simulated altitude/low pressure conditions and pump out rocket exhaust products. </p> <p>This dissertation combined experimental and numerical efforts on diffuser-ejector systems. The experimental efforts included the development of a Second Throat Exhaust Diffuser (STED) to aid with the qualification of space thrusters in the Purdue Altitude Chamber Facility. While performing these experiments, we characterized the single and two-stage ejector systems operating in conjunction with the diffuser to obtain and maintain specific simulated altitudes. </p> <p>The concurrent numerical effort focused on validating a Computational Fluid Dynamics (CFD) approach based on Reynolds-averaged Navier–Stokes equations flow simulations. After validating the ejector CFD, we used it to derive a corrective coefficient of a lumped parameter ejector model (LPM) developed previously for the ejectors used in the Purdue Altitude Facility. We created variable coefficient maps for the stages of the two-stage ejector system using the same LPM and the test data from one of our experiments. </p> <p>We designed, manufactured, and then validated a STED for altitude testing of a ~50 lbf hypergolic hybrid motor as a part of a NASA JPL project. The designed STED enabled the operation of the hybrid motor for the full duration of the test firing (about 2 seconds) at a simulated altitude of 102,000 feet, slightly above the targeted altitude of 100,000 feet. We also validated our diffuser CFD approach by creating a simulation using the measured diffuser back pressure and the average motor chamber pressure. </p> <p>We then devised an experiment to investigate several diffuser–ejector system configurations using cold gas thrusters with conical and bell nozzles. The main aim of that experiment was to explore the effects of different thruster nozzle geometries, diffuser geometries, and thruster/ejector operational parameters on the performance of a diffuser–ejector system. For all the configurations tested, we reported on the minimum starting and operating pressure ratios and corresponding correction factors on the normal shock method. The large hysteresis regions obtained mostly with bell nozzles having a high initial expansion angle provided an opportunity to economize the facility resources. In some cases which were later found to violate STED second throat contraction limits, we experienced a choking flow at the second throat. Then, we studied the second throat contraction limits in detail using CFD in addition to the experimental data and explored minimum diffuser second throats enabling diffuser starting and improving aerodynamic efficiency. </p> <p>Finally, we machined a larger scale cold gas thruster with different nozzle geometries (having throat diameters in the range of 0.367 – 0.52 inches) from acrylic rods to study possible flow separation and gas condensation events that could occur during tests in the altitude chamber. The main difference here with the previous experiment was that the diffuser (JPL STED) was fixed, and the two-stage ejector system was used to create the necessary back pressure. With the experiments performed at varying axial gaps between the nozzle exit and diffuser inlet, we were able to investigate the effect of that on the diffuser performance. The experimental data collected in this work and the complementary numerical efforts served to generate the operating envelope of the Purdue Altitude Chamber Facility.  </p>