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At least 1,315 records · Page 73

A model for the prediction of latent errors using data obtained during the development process

A model implemented in a program that runs on the IBM PC for estimating the latent (or post ship) content of a body of software upon its initial release to the user is presented. The model employs the count of errors discovered at one or more of the error discovery processes during development, such as a design inspection, as the input data for a process which provides estimates of the total life-time (injected) error content and of the latent (or post ship) error content--the errors remaining a delivery. The model presented presumes that these activities cover all of the opportunities during the software development process for error discovery (and removal).

Gaffney, J. E., Jr.↗

Landform Evolution Modeling of Sedimentary Processes on Icy Worlds: the Cases of Hyperion and Helene

Sedimentary activity (erosion, transportation and deposition) is a major landscape-shaping process on many icy worlds of the outer solar system for which an understanding of this process is central to their geologic characterizations. Several recent studies, lead by the authors, have identified the effects of sedimentary activity on icy satellite landforms and recognized the role of mass wasting and volatile loss and redistribution in the evolution of these features. We apply state of the art, physics based, landform evolution modeling to icy satellite sedimentary landforms in order to fully quantitatively characterize how their morphologies change with time, and what their present appearances imply for the initial abundance and distribution of loose material, volatiles, and refractories in original pristine landforms. We will present results of our landform evolution modeling to the development of the landscapes of the Saturnian moons of Hyperion and Helene. Our current conclusions for Hyperion are that its unique appearance can be explained in part by the loss to space of ballistic ejecta during impact events. In order to create the smooth surfaces and the reticulate, honeycomb pattern of narrow divides between old craters, appreciable subsequent modification of crater morphology must occur through mass-wasting processes accompanied by sublimation, probably facilitated by the loss of CO2 as a component of the relief-supporting matrix of the bedrock. This mass wasting effectively destroys small craters, at least in part accounting for the paucity of sub-kilometer craters on Hyperion. Helene’s unusual morphology consists of broad depressions (modified large craters) and a generally smooth surface patterned with streaks and grooves. The streaks appear to be oriented down-gradient, as are the grooves. This pattern suggests intensive mass-wasting as a dominant process. Our initial modeling of this surface suggests a Bingham-like rheological behavior for the loose down-slope moving material. Interestingly, as a Bingham flow, the models indicate that aperiodic "intermittent" behavior to be present, suggesting that periods of quiet steady landform evolution are punctuated short periods of active surface readjustment.

Saturnian moons↗

Trash Compaction and Processing System Trash Models and Evolved Gas Analysis of Trash Components

As part of the NASA Next Space Technologies for Exploration Partnerships (NextSTEP) Trash Compaction and Processing System (TCPS) program, the Generation 2 (Gen 2) Heat Melt Compactor (HMC) tests a variety of trash models (nominal, high liquid, and high cloth) in order to evaluate the technical risk associated with processing spacecraft trash. The trash components used in the trash models not only impacts the final solid trash disk quality, but also the water and gas effluent compositions. In order to better design an auxiliary system to treat the effluent streams, both the input trash components and the effluent must be characterized. Evolved gas analysis (EGA) methods are used to characterize the input trash components. The EGA results will be used to determine various HMC operational parameters, as well as to determine the optimal operation for the TCPS system.

Heat Melt Compactor↗

International collaboration in disposal research: comparative modeling of coupled processes in the DECOVALEX project

Abstract. This presentation gives an overview of an international research collaboration for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems. The creation of the international DECOVALEX project, now running for more than 25 years, was motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. DECOVALEX emphasizes joint analysis and comparative modeling of state-of-the-art field and laboratory experiments, across a range of host rock options and repository designs. Participating research teams are from radioactive waste management organizations, national research institutes, regulatory agencies, universities, and consulting groups, providing a wide range of perspectives and solutions to these complex problems. The presentation provides examples of the research contributions made collectively in past DECOVALEX tasks and also touches on the unique modeling challenges tackled in the ongoing project phase, referred to as DECOVALEX-2023. The current phase comprises 17 partner organizations, about 50 modeling teams, and 7 modeling tasks, which cover a broad portfolio from fundamental studies on gas migration to full-scale in situ heater experiments in different host rocks to performance assessment studies. Together, these examples illustrate that the insight and scientific knowledge gained within the DECOVALEX project would not have been possible if one group had studied these complex THMC modeling challenges alone rather than within a truly collaborative setting.

Birkholzer, Jens T.↗

Computational Modeling in Structural Materials Processing

High temperature materials such as silicon carbide, a variety of nitrides, and ceramic matrix composites find use in aerospace, automotive, machine tool industries and in high speed civil transport applications. Chemical vapor deposition (CVD) is widely used in processing such structural materials. Variations of CVD include deposition on substrates, coating of fibers, inside cavities and on complex objects, and infiltration within preforms called chemical vapor infiltration (CVI). Our current knowledge of the process mechanisms, ability to optimize processes, and scale-up for large scale manufacturing is limited. In this regard, computational modeling of the processes is valuable since a validated model can be used as a design tool. The effort is similar to traditional chemically reacting flow modeling with emphasis on multicomponent diffusion, thermal diffusion, large sets of homogeneous reactions, and surface chemistry. In the case of CVI, models for pore infiltration are needed. In the present talk, examples of SiC nitride, and Boron deposition from the author's past work will be used to illustrate the utility of computational process modeling.

Meyyappan, Meyya↗

Modeling of membrane processes for air revitalization and water recovery

Gas-separation and reverse-osmosis membrane models are being developed in conjunction with membrane testing at NASA JSC. The completed gas-separation membrane model extracts effective component permeabilities from multicomponent test data, and predicts the effects of flow configuration, operating conditions, and membrane dimensions on module performance. Variable feed- and permeate-side pressures are considered. The model has been applied to test data for hollow-fiber membrane modules with simulated cabin-air feeds. Results are presented for a membrane designed for air drying applications. Extracted permeabilities are used to predict the effect of operating conditions on water enrichment in the permeate. A first-order reverse-osmosis model has been applied to test data for spiral wound membrane modules with a simulated hygiene water feed. The model estimates an effective local component rejection coefficient under pseudosteady-state conditions. Results are used to define requirements for a detailed reverse-osmosis model.

Lange, Kevin E.↗

FORCE Integration with DRAFT and IDAES

Integrated energy systems (IES) combine, in mutually beneficial ways, power from variable renewable energy sources and nuclear power plants (NPP) to produce multiple commodities and improve economic viability under uncertain market conditions. Technical and economic analysis of IES requires modeling of complex processes with software models having enough fidelity to capture real-world dynamics while still being capable of running using reasonable computing resources. The open-source Framework for Optimization of Resources and Economics (FORCE) tool suite, developed at Idaho National Laboratory (INL), has enabled comprehensive modeling and simulation of IES. The capabilities within FORCE include grid portfolio optimization through the Holistic Energy Resource Optimization Network (HERON) and the transient process model analysis library HYBRID, among others. Recent developments for the FORCE toolset have centered on strengthening the flexibility and modularity to link with external models and other available software to enhance IES simulations. Adding versatility to the FORCE toolset improves capability resulting in better techno-economic simulation of nuclear and IES components (both in potential higher fidelity and accuracy to expected performance after deployment). It also helps leverage existing work in the IES field and improve efficiency in national code development. This report focuses on two such endeavors: integration of the Dynamic Reliability Analysis Framework Tool (DRAFT) and the Design Integration and Synthesis Platform to Advance Tightly Coupled Hybrid Energy Systems (DISPATCHES) software packages into FORCE.

97 MATHEMATICS AND COMPUTING↗

Information processing

Theoretical models of sensory-information processing by the human brain are reviewed from a human-factors perspective, with a focus on their implications for aircraft and avionics design. The topics addressed include perception (signal detection and selection), linguistic factors in perception (context provision, logical reversals, absence of cues, and order reversals), mental models, and working and long-term memory. Particular attention is given to decision-making problems such as situation assessment, decision formulation, decision quality, selection of action, the speed-accuracy tradeoff, stimulus-response compatibility, stimulus sequencing, dual-task performance, task difficulty and structure, and factors affecting multiple task performance (processing modalities, codes, and stages).

Wickens, Christopher D.↗

Modelica-json: Transforming energy models to digitize the control delivery process

Building simulation models are typically not used to generate the documentation required for bidding and project delivery of commercial building systems, or for their semantic modeling and commissioning. This paper presents a software tool that aids in digitizing the control delivery process, spanning simulation during design to implementation and formal verification during commissioning. The tool can generate from Modelica models digital documentation of control sequences. This digital documentation, along with other project drawings and specifications can be used for project bidding. It can also be used for implementation of control sequences through machineto-machine translation to commercial legacy control products, for which we are currently developing the proposed ASHRAE Standard 231P based on the presented work. Moreover, as-installed control sequences can be formally verified against the design specification, and a semantic model in Brick can be exported to aid in configuration of building analytics and fault detection. The paper presents what we believe is the first translation of a Modelica-implemented control sequence to a native implementation on a commercial control platform, using the webCTRL product line from Automated Logic. The paper also shows how a webCTRL implementation can be formally verified against its Modelica specification. These use cases have all been demonstrated with a prototype implementation that is now being further developed.

Wetter, Michael↗

Reinventing the Design Process: Teams and Models

The future of space mission designing will be dramatically different from the past. Formerly, performance-driven paradigms emphasized data return with cost and schedule being secondary issues.

Design↗

Hyperplane decision trees as piecewise linear surrogate models for chemical process design

Recent trends in chemical engineering research point towards an increasing reliance on data-driven modeling approaches. Neural networks, for instance, have proven to be accurate when data is plentiful and high-dimensional, but in many cases, they require computationally-intensive training procedures. Here, in this work, we describe hyperplane decision trees (HT) as a highly expressive and low-compute machine learning model architecture. These models are locally linear and have linear decision boundaries, resulting in a piecewise linear model of the data. This property allows them to be converted into mixed-integer linear constraints which can be globally optimized. Our open-source PyTorch implementation of this method is a fast, flexible, and accessible way to build accurate piecewise linear models of data.

Decision trees↗

Leaf optical system modeled as a stochastic process

A stochastic leaf radiation model based upon physical and physiological properties of dicot leaves has been developed. The model accurately predicts the absorbed, reflected, and transmitted radiation of normal incidence as a function of wavelength resulting from the leaf-irradiance interaction over the spectral interval of 0.40-2.50 micron. The leaf optical system has been represented as Markov process with a unique transition matrix at each 0.01-micron increment between 0.40 micron and 2.50 micron. Probabilities are calculated at every wavelength interval from leaf thickness, structure, pigment composition, and water content. Simulation results indicate that this approach gives accurate estimations of actual measured values for dicot leaf absorption, reflection, and transmission as a function of wavelength.

Tucker, C. J.↗

A SLAM II simulation model for analyzing space station mission processing requirements

Space station mission processing is modeled via the SLAM 2 simulation language on an IBM 4381 mainframe and an IBM PC microcomputer with 620K RAM, two double-sided disk drives and an 8087 coprocessor chip. Using a time phased mission (payload) schedule and parameters associated with the mission, orbiter (space shuttle) and ground facility databases, estimates for ground facility utilization are computed. Simulation output associated with the science and applications database is used to assess alternative mission schedules.

Linton, D. G.↗

Dawn Orbit Determination Team: Trajectory Modeling and Reconstruction Processes at Vesta

The Dawn spacecraft spent over a year in orbit around Vesta from July 2011 through August 2012. In order to maintain the designated science reference orbits and enable the transfers between those orbits, precise and timely orbit determination was required. Challenges included low-thrust ion propulsion modeling, estimation of relatively unknown Vesta gravity and rotation models, track-ing data limitations, incorporation of real-time telemetry into dynamics model updates, and rapid maneuver design cycles during transfers. This paper discusses the dynamics models, filter configuration, and data processing implemented to deliver a rapid orbit determination capability to the Dawn project.

low thrust↗

Multiscale Modeling of Damage Processes in Aluminum Alloys: Grain-Scale Mechanisms

This paper has two goals related to the development of a physically-grounded methodology for modeling the initial stages of fatigue crack growth in an aluminum alloy. The aluminum alloy, AA 7075-T651, is susceptible to fatigue cracking that nucleates from cracked second phase iron-bearing particles. Thus, the first goal of the paper is to validate an existing framework for the prediction of the conditions under which the particles crack. The observed statistics of particle cracking (defined as incubation for this alloy) must be accurately predicted to simulate the stochastic nature of microstructurally small fatigue crack (MSFC) formation. Also, only by simulating incubation of damage in a statistically accurate manner can subsequent stages of crack growth be accurately predicted. To maintain fidelity and computational efficiency, a filtering procedure was developed to eliminate particles that were unlikely to crack. The particle filter considers the distributions of particle sizes and shapes, grain texture, and the configuration of the surrounding grains. This filter helps substantially reduce the number of particles that need to be included in the microstructural models and forms the basis of the future work on the subsequent stages of MSFC, crack nucleation and microstructurally small crack propagation. A physics-based approach to simulating fracture should ultimately begin at nanometer length scale, in which atomistic simulation is used to predict the fundamental damage mechanisms of MSFC. These mechanisms include dislocation formation and interaction, interstitial void formation, and atomic diffusion. However, atomistic simulations quickly become computationally intractable as the system size increases, especially when directly linking to the already large microstructural models. Therefore, the second goal of this paper is to propose a method that will incorporate atomistic simulation and small-scale experimental characterization into the existing multiscale framework. At the microscale, the nanoscale mechanics are represented within cohesive zones where appropriate, i.e. where the mechanics observed at the nanoscale can be represented as occurring on a plane such as at grain boundaries or slip planes at a crack front. Important advancements that are yet to be made include: 1. an increased fidelity in cohesive zone modeling; 2. a means to understand how atomistic simulation scales with time; 3. a new experimental methodology for generating empirical models for CZMs and emerging materials; and 4. a validation of simulations of the damage processes at the nano-micro scale. With ever-increasing computer power, the long-term ability to employ atomistic simulation for the prognosis of structural components will not be limited by computation power, but by our lack of knowledge in incorporating atomistic models into simulations of MSFC into a multiscale framework.

Hochhalter, J. D.↗