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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Provably accurate simulation of gauge theories and bosonic systems

Quantum many-body systems involving bosonic modes or gauge fields have infinite-dimensional local Hilbert spaces which must be truncated to perform simulations of real-time dynamics on classical or quantum computers. To analyze the truncation error, we develop methods for bounding the rate of growth of local quantum numbers such as the occupation number of a mode at a lattice site, or the electric field at a lattice link. Our approach applies to various models of bosons interacting with spins or fermions, and also to both abelian and non-abelian gauge theories. We show that if states in these models are truncated by imposing an upper limit Λ on each local quantum number, and if the initial state has low local quantum numbers, then an error at most ϵ can be achieved by choosing Λ to scale polylogarithmically with ϵ − 1 , an exponential improvement over previous bounds based on energy conservation. For the Hubbard-Holstein model, we numerically compute a bound on Λ that achieves accuracy ϵ , obtaining significantly improved estimates in various parameter regimes. We also establish a criterion for truncating the Hamiltonian with a provable guarantee on the accuracy of time evolution. Building on that result, we formulate quantum algorithms for dynamical simulation of lattice gauge theories and of models with bosonic modes; the gate complexity depends almost linearly on spacetime volume in the former case, and almost quadratically on time in the latter case. We establish a lower bound showing that there are systems involving bosons for which this quadratic scaling with time cannot be improved. By applying our result on the truncation error in time evolution, we also prove that spectrally isolated energy eigenstates can be approximated with accuracy ϵ by truncating local quantum numbers at Λ = polylog ( ϵ − 1 ) .

Tong, Yu↗
DOE OSTI2026

Hygrothermal Performance of Bio-Based Materials in Residential Building Wall Envelope Systems

In the United States, building envelope systems contribute approximately 28% of building energy consumption, with walls being a primary factor. As the construction industry explores new approaches to lower the energy intensity needed to manufacture materials and, in turn, reduce energy consumption, bio-based materials are gaining attention as a promising alternative. While prior studies have demonstrated that bio-based materials can decrease material energy intensity, their long-term hygrothermal behavior within a whole residential wall system is not yet fully understood. This study aims to evaluate the potential of replacing Oriented Strand Board (OSB) and drywall in residential wall systems with bio-based alternatives. The research focuses on two bio-based materials, assessing their hygrothermal performance under Chicago climate condition (Climate Zone 5). To achieve that, a series of laboratory experiments were conducted to measure key properties of the bio-based materials such as thickness, dimensions, density, thermal conductivity (as a function of temperature and humidity), moisture-dependent permeance and water vapor permeability (WVP), and sorption isotherms. These properties were then used in WUFI® simulations to predict the moisture durability of a standard residential wall system in Climate Zone 5. Results show that substituting OSB and drywall with bio-based materials can achieve acceptable moisture durability, effectively mitigating risks of mold growth and structural damage over time.

Palani, Hevar [ORNL] (ORCID:0000000220211994)↗
NASA NTRS1997

Ring Buffered Network Bus

This report describes the research effort to demonstrate the integration of a data sharing technology, Ring Buffered Network Bus, in development by Dryden Flight Research Center, with an engine simulation application, the Java Gas Turbine Simulator, in development at the University of Toledo under a grant from the Glenn Research Center. The objective of this task was to examine the application of the RBNB technologies as a key component in the data sharing, health monitoring and system wide modeling elements of the NASA Aviation Safety Program (AVSP) [Golding, 1997]. System-wide monitoring and modeling of aircraft and air safety systems will require access to all data sources which are relative factors when monitoring or modeling the national airspace such as radar, weather, aircraft performance, engine performance, schedule and planning, airport configuration, flight operations, etc. The data sharing portion of the overall AVSP program is responsible for providing the hardware and software architecture to access and distribute data, including real-time flight operations data, among all of the AVSP elements. The integration of an engine code capable of numerically "flying" through recorded flight paths and weather data using a software tool that allows for distributed access of data to this engine code demonstrates initial steps toward building a system capable of monitoring and modeling the National Airspace.

Source record↗
NASA NTRS2022

On-board Absolute Localization Based on Orbital Imagery for a Future Mars Science Helicopter

Future Mars Rotorcraft require advanced navigationcapabilities to enable all terrain access over long distance flightsthat are executed fully autonomously. A critical component toenable precision navigation during long traverses is the abilityto perform on-board absolute localization to eliminate drift inposition estimates of the on-board odometry algorithm. Inthis paper, we present an approach for on-board map-basedlocalization to provide global reference position based on orbitalor aerial image maps. Our approach builds on a vision-basedlocalization method to localize against a map derived fromHiRISE image products – an ortho-projected image (orthoimage) and a corresponding digital elevation map. The mapis pre-computed using a feature-based approach. Features arestored with their 3D world coordinates, and a descriptor to codethe local image intensity information in the vicinity of the featurelocation. An on-board matching algorithm uses this informationto match visual features in a query image acquired during flight,guided by a pose prior from the on-board range-visual-inertialstate estimator (Range-VIO). Valid matches are then used bya perspective-n-point (PnP) algorithm to estimate the absolutepose of the vehicle in a global frame. We demonstrate andevaluate our approach on simulated data, and data from UASflights.

Balaram, J. Bob↗
DOE OSTI2021

Machine Learning Assisted Safety Modeling and Analysis of Advanced Reactors

With the advances in computational power and numerical methods, analysts can now rely on first-principle simulations to predict ultra-fine details in a variety of applications. Advances in machine learning (ML) have produced algorithms that can now learn high-level abstractions via hierarchical models. This project aims to leverage advances in ML techniques and the available high-resolution simulation data to develop a novel modeling and simulation (M\&S) methodology for reactor safety analysis. While application-agnostic ML techniques are available, complex physics constraints need to be incorporated into ML techniques to build ML-based closures for computationally efficient predictive simulations. This project intends to develop a physics-guided data-driven multi-scale methodology for M\&S of advanced reactors. The project focuses on thermal fluid (T/F) phenomena, which play major roles in advanced reactor safety. Specifically, we propose a data-driven coarse-mesh turbulence model based on local flow features for the transient analysis of thermal mixing and stratification in a sodium-cooled fast reactor (SFR). The model has a coarse-mesh setup to ensure computational efficiency, while it is trained by fine-mesh computational fluid dynamics (CFD) data with Reynolds-averaged Navier-Stokes (RANS) turbulence model to ensure accuracy. Three different neural networks are developed and tested for loss-of-flow transients in the hot pool of SFR, i.e. the densely connected convolutional neural network (DCNN), long-short-term-memory network based on proper orthogonal decomposition (POD-LSTM), and the DCNN informed by LSTM (DCNN-LSTM). The performances of these three neural networks are evaluated based on baseline models. The DCNN-LSTM model has been chosen for further hyperparameter optimization. Furthermore, based on a simplified two-dimensional case, uncertainty quantification (UQ) of the developed ML-based closure are investigated with three methods, i.e. Monte Carlo dropout, deep ensemble, and Bayesian neural network. The developed ML-based turbulent viscosity closure relation based on deep ensemble is then integrated into the system analysis module SAM and serves as a term in the conservation equations. Such a SAM-ML based procedure guarantees that the obtained results are consistent with the physical constraints of the thermal-fluid system. The SAM-ML simulation on the same loss-of-flow transient showed comparable accuracy with the CFD simulation but with a much coarser mesh setup. Last but not least, the ML-based closure improvement with the support of higher-fidelity data from large eddy simulation (LES) is discussed. As a first step towards this direction, a baseline LES simulation is performed to obtain comparable data with RANS results. Based on the early results, future investigation on further improving the ML-based closure is discussed. We believe the developed approach that combines scientific machine learning with nuclear system analysis code can benefit the advanced reactor community as more accurate safety analyses will better characterize reactor safety margins and reduce licensing efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

NORTH DAKOTA CARBONSAFE PHASE III: SITE CHARACTERIZATION AND PERMITTING OF GEOLOGIC STORAGE OF CARBON DIOXIDE

The Energy & Environmental Research Center (EERC), in partnership with Minnkota Power Cooperative Inc. (Minnkota), SLB, and Computer Modelling Group Ltd. (CMG), supported wide-scale deployment of carbon capture and storage (CCS) as part of the U.S. Department of Energy (DOE) National Energy Technology Laboratory Carbon Storage Assurance Facility Enterprise (CarbonSAFE) Initiative Phase III. This phase included the acquisition, analysis, and development of information to fully characterize two storage complexes to demonstrate viable storage resources for commercial volumes of CO2 (defined by DOE as a minimum of 50 million tonnes [MMt] of CO2 within a 30-year period) (National Energy Technology Laboratory, 2024). Phase III also involved the preparation, submission, and approval of North Dakota underground injection control (UIC) Class VI storage facility permits (SFPs)—required precursors to applications for Class VI injection well permits. The presumed viability of commercial-scale CCS, situated adjacent to Minnkota’s Milton R. Young Station (MRYS), is validated by Minnkota’s continued pursuit of Project Tundra—an initiative to build the world’s largest lignite-based CCS project in central North Dakota (www.projecttundrand.com). Project Tundra comprises two scopes of work, Tundra Capture (installation of postcombustion CO2 capture at MRYS) and Tundra SGS (secure geologic storage). The efforts of North Dakota CarbonSAFE Phase III, Site Characterization and Permitting, supported Tundra SGS. Extensive site-specific characterization activities included a successful multimeasurement geophysical approach and drilling a stratigraphic test well (J-ROC 1, subsequently renamed Liberty-1) adjacent to MRYS. Core collection and analyses, downhole testing and fluid sampling, and geophysical logging were performed on J-ROC 1 and on a nearby stratigraphic test well (known as J-LOC 1), which was drilled, cored, and tested under a complementary project funded by the North Dakota Lignite Research Program. The injection tests performed on J-LOC 1 positively impacted the CarbonSAFE project, resulting in fewer proposed injection wells and significant construction, operations, and monitoring cost savings. The characterization data collected and analyses performed were integrated into geologic models, and successive numerical simulations were run to determine CO2 plume extent and subsurface pressure buildup associated with the planned CO2 injection rate of nearly 4 MMt per year. The latter doubles the CarbonSAFE Initiative goal with an estimated 100 MMt of CO2 stored in 20 years. Application of the U.S. Environmental Protection Agency’s (EPA’s) method for estimating the Class VI Rule area of review (AOR) to the overpressurized Broom Creek Formation inspired an alternative method of calculation, called risk-based AOR delineation. This peer-reviewed method was applied for the first time during the storage facility-permitting process. The two SFP applications submitted in 2021 successfully resulted in North Dakota Industrial Commission (NDIC) orders in 2022 authorizing the creation of the storage facility areas and amalgamation of pore space as well as establishing financial responsibility requirements. After approval of the SFPs, Minnkota filed in 2022 applications for permits to reenter the J-ROC 1 well and to drill two new wells—all with the intended purpose to become Class VI injection wells. To establish eligibility under the Internal Revenue Code for Section 45Q tax incentives, a monitoring, reporting, and verification (MRV) plan was prepared and submitted by Minnkota to EPA in 2022, resulting in the first such plan approved in North Dakota. Also in 2022, under the National Environmental Policy Act (NEPA), Minnkota prepared and submitted an environmental information volume (EIV) describing the proposed CCS project and associated potential environmental impacts. Based on the EIV, DOE determined that the proposed construction project required an environmental assessment, and Minnkota submitted the first draft in 2023 and a revised draft in 2024. Both submissions were followed by a public comment period. Subsequently, DOE issued a finding of no significant impact (FONSI) on September 13, 2024. A successful outreach program, strongly based in the production, presentation, and dissemination of informational material, fostered an environment to aid stakeholders in making informed decisions regarding the planned project. Opportunities for public input were provided at various steps along the way, including at county planning and zoning meetings, before and during the SFP administrative hearing, and during environmental assessment public comment periods. In addition, land/pore space owners and mineral owners had various points of contact, including granting access rights, securing pore space leasing, and mineral owner notifications. Based upon the successful storage facility permitting issued by NDIC, approval of the MRV plan by EPA, and receipt of a FONSI under the NEPA, Minnkota is continuing its pursuit of Project Tundra. In December 2023, the Office of Clean Energy Demonstrations under its Carbon Capture Demonstrations Projects Program announced funding for the capture system (Office of Clean Energy Demonstrations, 2023) and a proposal for CarbonSAFE Phase IV: Construction funding was submitted in March 2024 for the storage project. A go/no-go decision to proceed with construction and operations in the Broom Creek Formation is anticipated in 2024. References National Energy Technology Laboratory, CarbonSafe Initiative, https://netl.doe.gov/carbon-management/carbon-storage/carbonsafe (accessed August 2024). Office of Clean Energy Demonstrations, 2023, OCED selects three projects in CA, ND, and TX to reduce harmful carbon pollution, create new economic opportunities, and advance carbon reducing technologies, December, www.energy.gov/oced/articles/oced-selects-three-projects-ca-nd-and-tx-reduce-harmful-carbon-pollution-create-new (accessed August 2024).

Peck, Wesley↗
NASA NTRS1990

A3I visibility modeling project

The Army-NASA Aircrew Aircraft Integration program is supporting a joint project to build a visibility computer-aided design (CAD) tool. CAD has become an essential tool in modern engineering applications. CAD tools are used to create engineering drawings and to evaluate potential designs before they are physically realized. The visibility CAD tool will provide the design engineer with a tool to aid in the location and specification of windows, displays, and control in crewstations. In an aircraft cockpit the location of instruments and the emissive and reflective characteristics of the surfaces must be determined to assure adequate aircrew performance. The visibility CAD tool will allow the designer to ask and answer many of these questions in the context of a three-dimensional graphical representation of the cockpit. The graphic representation of the cockpit is a geometrically valid model of the cockpit design. A graphic model of a pilot, called the pilot manikin, can be placed naturalistically in the cockpit model. The visibility tool has the capability of mapping the cockpit surfaces and other objects modeled in this graphic design space onto the simulated pilot's retinas for a given visual fixation.

Larimer, James↗
NASA NTRS2013

Carbon Dioxide: Surprising Effects on Decision Making and Neurocognitive Performance

The occupants of modern submarines and the International Space Station (ISS) have much in common as far as their air quality is concerned. Air is polluted by materials offgassing, use of utility compounds, leaks of systems chemicals, and anthropogenic sources. The primary anthropogenic compound of concern to submariners and astronauts has been carbon dioxide (CO2). NASA and the US Navy rely on the National Research Council Committee on Toxicology (NRC-COT) to help formulate exposure levels to CO2 that are thought to be safe for exposures of 3-6 months. NASA calls its limits Spacecraft Maximum Allowable Concentrations (SMACs). Years of experience aboard the ISS and a recent publication on deficits in decision making in ground-based subjects exposed briefly to 0.25% CO2 suggest that exposure levels that have been presumed acceptable to preserve health and performance need to be reevaluated. The current CO2 exposure limits for 3-6 months set by NASA and the UK Navy are 0.7%, and the limit for US submariners is 0.5%, although the NRC-COT recommended a 90-day level of 0.8% as safe a few years ago. NASA has set a 1000-day SMAC at 0.5% for exploration-class missions. Anecdotal experience with ISS operations approaching the current 180-day SMAC of 0.7% suggest that this limit is too high. Temporarily, NASA has limited exposures to 0.5% until further peer-reviewed data become available. In the meantime, a study published last year in the journal Environmental Health Perspectives (Satish U, et al. 2012) demonstrated that complexdecision- making performance is somewhat affected at 0.1% CO2 and becomes "dysfunctional" for at least half of the 9 indices of performance at concentrations approaching 0.25% CO2. The investigators used the Strategic Management Simulation (SMS) method of testing for decisionmaking ability, and the results were so surprising to the investigators that they declared that their findings need to be independently confirmed. NASA has responded to the findings on decision making by developing a study to either confirm or refute the published results. In addition, other neurocognitive tests that have been and will be used aboard the ISS will be part of the ground-based study. Further evaluations during the exposures will include ocular and cardiovascular effects of CO2 exposure. In addition, the 1- carbon genetics of the test subjects will be evaluated to determine if any individual subjects are unusually susceptible to CO2 exposure because of genetic factors. Our plan is to extend the published study from Satish by employing a wider series of CO2 exposures to include concentrations of 0.06, 0.12, 0.25, and 0.50%. We believe that our findings will be of keen interest to submariners and to those designing "tight" buildings.

James, John T.↗
NASA NTRSDate not supplied

Uncertainty Quantification using Deep Ensembles for Decision Making in Cyber-Physical-Human Systems

In this paper and its companion, Differential Equation Approximation Using Gradient-Boosted Quantile Regression, Robison et al., we examine an approach to quantifying model uncertainty with the aim of increasing the trustworthiness of computational models in human-machine interactions. In Differential Equation Approximation Using Gradient-Boosted Quantile Regression, we focus on gradient-boosted decision trees, while in this one, we give more details about deep ensembles. Uncertainty quantification is crucial for building trustworthy autonomous decision-making agents in human-machine teams. There are two types of uncertainties: aleatoric and epistemic. The former is related to the inherent stochasticity (noise) of the process, whereas the latter is associated with the lack of knowledge or representation capability of models, such as neural networks. By lack of knowledge, we mean the model’s inability to accurately predict outputs for all possible inputs. The aleatory uncertainty can be estimated fairly easily with, for example, filters, whereas epistemic uncertainty is challenging to compute. This paper uses deep ensembles to quantify both aleatory and epistemic uncertainty. It can act as an uncertainty-aware surrogate transition model for decision-making frameworks. "Uncertainty-aware" means that the surrogate transition model should make predictions along with confidence in those predictions. In the context of decision-making, the transition models are ordinary differential equations (ODEs). Since ODEs can be simulated to make one-step or multi-step predictions, a good surrogate model for them should perform reasonably well in both modes. In a multi-step approach, the trajectory sampling method TS∞ was used to propagate uncertainty over multiple steps. The cartpole dynamical system was selected to demonstrate the ability of deep ensembles as good surrogate transition models for decision-making frameworks. The deep ensembles modeled the dynamics of cartpole ODEs and made uncertainty-aware predictions in single-step and multi-step transition modes.

CPH systems↗
NASA NTRSDate not supplied

Perturbation Modeling and Navigation Tuning for a Crewed Station in Near Rectilinear Halo Orbit

NASA's Gateway program will build a crew-tended station in an Earth-Moon Near Rectilinear Halo Orbit (NRHO) to support deep space missions to the lunar surface and heliocentric space. The station in the NRHO will be visited by crewed vehicles including lunar landers that are high mass relative to Gateway. Docking events with large vehicles induce significant thruster plume and docking contact velocity perturbations. Crewed vehicles induce significant venting perturbations that can stress the navigation filter's ability to remain converged about an estimated state. The torques that arise from venting and lunar gravity gradient require reaction control system (RCS) thruster intervention, which themselves induce a velocity perturbation. The best method to model RCS thruster perturbations is currently in development. This paper simulates different RCS perturbation models, schedules, and an increasing magnitude to investigate the navigation sensitivity to different RCS perturbation models. From the RCS perturbation models simulated, a worst-case scenario is chosen for further scrutiny. The navigation filter is further tuned to handle the most disruptive perturbation modeling and the resulting performance is analyzed.

Navigation↗
DOE OSTI2021

Operating Hardware Impact on the Heat Transfer Properties of Windows

Despite significant advancements in fenestration technology in the last two decades, the thermal transmittance of fenestration products is still significantly higher than that of walls. This corresponds to 60% of the total energy loss of a modern building envelope through the windows. Hence, further development and improvements of fenestration products are necessary. Increasingly stringent codes and standards for fenestration stimulate industry to work on improved solutions. Thus, it is crucial that assessment techniques are able to account for innovations accurately. The thermal effects of non-continuous hardware in window frames are currently ignored by international rating procedures. A preliminary investigation conducted by our team showed significant performance degradation in two of the three out-opening casement profiles caused by the presence of operating hardware. Frames with the structure made of vinyl and fiberglass consist of many air cavities that are penetrated by operating hardware made of highly conductive materials. In these frames, in order to have an accurate assessment, it may be required to employ three-dimensional modeling due to the convective nature of heat transfer within the cavities. However, in this study, we demonstrate that the three-dimensional (3D) effects of non-continuous hardware can be approximated accurately with simpler two-dimensional (2D) simulations. We then develop a simplified model based on weighted average capable of replacing the time- and computation-intensive 3D simulations with 2D simulations and validate it against market available frames and their corresponding hardware. Validation results show that our approximation technique results in discrepancies lower than 0.05 W/(m2K), or 3% of the total thermal transmittance. Thus, we conclude that simplified 2D simulation models may be used for predicting hardware impact in window frames with reasonable accuracy. As windows and glazing structures are becoming ever better thermally insulated, it is becoming even more important to be able to model the impact of the operating hardware on the total thermal performance in order to design the best windows possible and not let the operating hardware ruin an otherwise well-proven design, which is hence addressed in this study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2011

Shuttle Program Loads Integration: Going From Concept to Operations and Staying Successful

From the beginning of the Shuttle Program to its end, integrated loads and dynamics analyses and tests have been critical in shaping the vehicle design and operational decisions for NASA and its customers. Starting with scaled models and simple mathematical simulations of the structural dynamics, engineers defined the required structural stiffness and predicted the limit loads for each element of the system. Early structural tests provided reasonable confidence that the models and predictions were good. The first launch of the Space Shuttle brought surprises, though, when the ignition overpressure event caused a forward fuel tank support strut to buckle, among several unexpected effects. The launch pad and other ground equipment became an integral part of the system integration, especially where the acoustic and pressure environments of ignition and lift-off were concerned. Following the Challenger accident, operating limits were changed in response to new understandings of how the integrated system performed. Controlling loads while maximizing performance was a key tenet of the Performance Enhancement design process, which enabled construction of the International Space Station. During the return to flight after the Columbia accident, engineers grew to understand that loads during the roll maneuver were also important to the vehicle s structural margin and life. At this point the crawler transport from the Vehicle Assembly Building to the launch pad also became a part of the integrated loads analysis. Even in the last years of the Space Shuttle Program, new data still provided interesting insights into this complicated and fascinating spaceship. This paper will present some examples of the important findings by the team of specialists that supported the Integrated Loads and Dynamics Panel for the Space Shuttle Program.

Bernstein, Karen↗
DOE OSTI2025

A critical review of electrochemical heat pump technologies: Status, challenges, and perspectives

The development of advanced heat pump technologies is critical for reducing global energy consumption in the building sector, where space heating and cooling account for nearly 50% of energy use. Electrochemical heat pumps (EHPs) offer a promising alternative to vapor compression systems by enabling direct electrochemical-to-thermal energy conversion, often with environmentally benign working fluids that exhibit low or zero global warming potential (GWP). Prior literature has predominantly focused on chemically reactive heat pumps, while comprehensive assessments of electrochemical mechanisms remain limited. Here, this review addresses this gap by systematically evaluating the underlying principles, architectures, and performance metrics of EHP systems. Compared to conventional vapor compression systems, EHPs can achieve 10%-30% higher energy efficiency, with reported cooling coefficients of performance (COP c ) ranging from 3.5 to 14.3 under standard operating conditions. Despite these advantages, widespread adoption is hindered by challenges including membrane degradation, electrode fouling, sluggish redox kinetics, and elevated system-level capital costs. To address these limitations, the review outlines three research priorities: (i) the development of advanced membranes, catalysts, and electrode materials with enhanced chemical and mechanical stability; (ii) the application of molecular-level simulations for the rational design of high-performance redox-active working fluids; and (iii) the integration of advanced diagnostic techniques for real-time monitoring and sustained operation of EHPs. By consolidating recent advances and explicitly identifying technological and scientific gaps, this work uniquely contributes a comprehensive framework for guiding future electrochemical heat pump research and facilitating the transition to sustainable thermal management technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Veridical data science

Building and expanding on principles of statistics, machine learning, and scientific inquiry, we propose the predictability, computability, and stability (PCS) framework for veridical data science. Our framework, composed of both a workflow and documentation, aims to provide responsible, reliable, reproducible, and transparent results across the data science life cycle. The PCS workflow uses predictability as a reality check and considers the importance of computation in data collection/storage and algorithm design. It augments predictability and computability with an overarching stability principle. Stability expands on statistical uncertainty considerations to assess how human judgment calls impact data results through data and model/algorithm perturbations. As part of the PCS workflow, we develop PCS inference procedures, namely PCS perturbation intervals and PCS hypothesis testing, to investigate the stability of data results relative to problem formulation, data cleaning, modeling decisions, and interpretations. We illustrate PCS inference through neuroscience and genomics projects of our own and others. Moreover, we demonstrate its favorable performance over existing methods in terms of receiver operating characteristic (ROC) curves in high-dimensional, sparse linear model simulations, including a wide range of misspecified models. Finally, we propose PCS documentation based on R Markdown or Jupyter Notebook, with publicly available, reproducible codes and narratives to back up human choices made throughout an analysis. The PCS workflow and documentation are demonstrated in a genomics case study available on Zenodo.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Lightning testing at the subsystem level

Testing at the subsystem or black box level for lightning hardness is required if system hardness is to be assured at the system level. The often applied philosophy of lighting testing only at the system level leads to extensive end of the line design changes which result in excessive costs and time delays. In order to perform testing at the subsystem level two important factors must be defined to make the testing simulation meaningful. The first factor is the definition of the test stimulus appropriate to the subsystem level. Application of system level stimulations to the subsystem level usually leads to significant overdesign of the subsystem which is not necessary and may impair normal subsystem performance. The second factor is the availability of test equipment needed to provide the subsystem level lightning stimulation. Equipment for testing at this level should be portable or at least movable to enable efficient testing in a design laboratory environment. Large fixed test installations for system level tests are not readily available for use by the design engineers at the subsystem level and usually require special operating skills. The two factors, stimulation level and test equipment availability, must be evaluated together in order to produce a practical, workable test standard. The neglect or subordination of either factor will guarantee failure in generating the standard. It is not unusual to hear that test standards or specifications are waived because a specified stimulation level cannot be accomplished by in-house or independent test facilities. Determination of subsystem lightning simulation level requires a knowledge and evaluation of field coupling modes, peak and median levels of voltages and currents, bandwidths, and repetition rates. Practical limitations on test systems may require tradeoffs in lightning stimulation parameters in order to build practical test equipment. Peak power levels that can be generated at specified bandwidths with standard electrical components must be considered in the design and costing of the test system. Stimulation tests equipment and test methods are closely related and must be considered a test system for lightning simulation. A non-perfect specification that can be reliably and repeatedly applied at the subsystem test level is more desirable than a perfect specification that cannot be applied at all.

Luteran, Frank↗
DOE OSTI2024

The Grain Boundary Relaxation (GBR) Approach for Manufacturing High Strength Nanocrystalline Lightweight Metals

The overarching goal of the project was to conduct research and development work as proposed in the Statement of Project Objective (SOPO) of the award document DE-FE-0009116. The project had 4 tasks and 12 milestones. All the milestone deliverables were completed. The accomplishments of the project objectives and technical discussions are described in Sections 3 and 4, respectively. The modeling and simulation work indicated that to increase the strength and stability of nanocrystalline aluminum (Al), selection of dopants, such as Mg, is necessary. It was predicted that the crystallite size should be less than 50 nm to give high strength. On the basis of modeling, cryo-milling of Al was conducted with the addition of Mg as a function of different times. The crystallite size of the cryo-milled powders was determined by XRD and TEM. Both measurements showed that the actual crystallite size of the grain was <40 nm. The thermal stability of the grain size was established as a function of temperature. It was established that the grain size was < 50 nm up to 500C. The crystallite size of the bulk sample prepared by spark plasma sintering (SPS) and cold spray (CS) additive manufacturing was less than <40 nm. The mechanical properties of the bulk samples prepared by SPS and CS, showed excellent microhardness, good tensile properties (>200 MPa) with moderate ductility and improved fatigue performance. Adding yttria stabilized zirconia (YSZ) improved the build thick of the CS sample, however the YSZ was getting embedded into the sample. A highly dense SPS samples sent for 3rd party testing to the Innovation Testing Services showed a minimum hardness of 180 HV with an average tensile strength of 512.5 MPa. The high cycle fatigue tests also showed an endurance limit of 179.5 MPa. The Energy cost evaluations showed an overall energy cost of around $\$$17.05 for the cryomilling and SPS processes and the total manufacturing cost calculations of $\$$78.14 for 1 kg of sample. The energy cost to prepare a Kg of CS sample is $\$$17.60 and the overall manufacturing cost is $\$$86.85.

36 MATERIALS SCIENCE↗
NASA NTRS2002

Reliability and Productivity Modeling for the Optimization of Separated Spacecraft Interferometers

As technological systems grow in capability, they also grow in complexity. Due to this complexity, it is no longer possible for a designer to use engineering judgement to identify the components that have the largest impact on system life cycle metrics, such as reliability, productivity, cost, and cost effectiveness. One way of identifying these key components is to build quantitative models and analysis tools that can be used to aid the designer in making high level architecture decisions. Once these key components have been identified, two main approaches to improving a system using these components exist: add redundancy or improve the reliability of the component. In reality, the most effective approach to almost any system will be some combination of these two approaches, in varying orders of magnitude for each component. Therefore, this research tries to answer the question of how to divide funds, between adding redundancy and improving the reliability of components, to most cost effectively improve the life cycle metrics of a system. While this question is relevant to any complex system, this research focuses on one type of system in particular: Separate Spacecraft Interferometers (SSI). Quantitative models are developed to analyze the key life cycle metrics of different SSI system architectures. Next, tools are developed to compare a given set of architectures in terms of total performance, by coupling different life cycle metrics together into one performance metric. Optimization tools, such as simulated annealing and genetic algorithms, are then used to search the entire design space to find the "optimal" architecture design. Sensitivity analysis tools have been developed to determine how sensitive the results of these analyses are to uncertain user defined parameters. Finally, several possibilities for the future work that could be done in this area of research are presented.

Kenny, Sean↗
NASA NTRS2024

Experimental Studies on the Effect of Impact Processes on the Formation and Evolution of Amino Acids

Introduction: A critical step in the emergence of life on Earth was the synthesis of larger organic molecules from simple building blocks such as NH3, CO2, H2O, and CH3OH. The presence of amino acids and other complex organics in comets and meteorites demonstrates that widespread organic synthesis likely occurred across the early solar system. Building on previous work [e.g., 1-3], we systematically explore impact-driven chemical evolution of exogenous organics and their precursors. Collisional processes may also have provided a source of energy for the formation of more complex organics from endogenous building blocks. The high flux of impactors to Earth immediately prior to and during the origins of life suggests that impacts could have played a critical role. Key Questions: 1. How are the formation and evolution of amino acids affected by the presence of a mineral matrix during cometary and asteroidal impacts onto the early Earth? 2. Do some minerals (e.g., phyllosilicates) provide a more robust protective framework or reactive surface site for amino-acid formation and/or polymerization? 3. Does the abundance of ices and/or amino acids relative to that of the mineral matrix affect the formation and evolution of amino acids? 4. Are there impact velocities/shock pressures at which formation or polymerization of amino acids is favored or precluded? Experimental Approach: This study systematically examines the conditions under which amino acids and other organic molecules can form, be polymerized, and/or be destroyed during impact events into particulate regolith simulants. Variable parameters include the modal composition of this regolith (silicate matrices, ratios of ices, silicates, and amino acids) and impact velocities/shock pressures. Impacts experiments were performed using the two-stage light-gas gun (LGG), vertical gun (VG), and flat-plate accelerator (FPA) in the Experimental Impact Lab at JSC. FPA experiments were performed over a range of shock pressures (11.3-31.5 GPa) using CM chondrite simulant mixed with amino acids at ratios of 0:10, 1:10, 1:103, and 1:106 (amino acid:host). Techniques for mixing cometary ices have been optimized and test runs have been performed using the LGG (see figure below). Analysis: Post-impact, samples are heated in water to extract amino acids and peptides. Extracts are characterized via liquid chromatography-mass spectrometry (LC-MS) and the mineralogies of solid residues are characterized using X-ray diffraction, scanning electron microscopy and transmission electron microscopy. Additional LC-MS and mineralogical analyses are underway.

Eve L Berger↗