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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

BMC Caller: a webtool to identify and analyze bacterial microcompartment types in sequence data

Bacterial microcompartments (BMCs) are protein-based organelles found across the bacterial tree of life. They consist of a shell, made of proteins that oligomerize into hexagonally and pentagonally shaped building blocks, that surrounds enzymes constituting a segment of a metabolic pathway. The proteins of the shell are unique to BMCs. They also provide selective permeability; this selectivity is dictated by the requirements of their cargo enzymes. We have recently surveyed the wealth of different BMC types and their occurrence in all available genome sequence data by analyzing and categorizing their components found in chromosomal loci using HMM (Hidden Markov Model) protein profiles. To make this a “do-it yourself” analysis for the public we have devised a webserver, BMC Caller (https://bmc-caller.prl.msu.edu), that compares user input sequences to our HMM profiles, creates a BMC locus visualization, and defines the functional type of BMC, if known. Shell proteins in the input sequence data are also classified according to our function-agnostic naming system and there are links to similar proteins in our database as well as an external link to a structure prediction website to easily generate structural models of the shell proteins, which facilitates understanding permeability properties of the shell. Additionally, the BMC Caller website contains a wealth of information on previously analyzed BMC loci with links to detailed data for each BMC protein and phylogenetic information on the BMC shell proteins. Our tools greatly facilitate BMC type identification to provide the user information about the associated organism’s metabolism and enable discovery of new BMC types by providing a reference database of all currently known examples.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Multiscale-Informed Modeling of High Temperature Component Response with Uncertainty Quantification

This report summarizes a joint effort between Argonne National Laboratory, Idaho National Laboratory, and Los Alamos National Laboratory to develop and deploy constitutive models targeted at predicting the life of Grade 91 alloy components subjected to high temperature environments typical of those that structural components in advanced nuclear reactors would experience. Two distinct, but complementary constitutive modeling approaches have been taken here. The first employs a phenomenological viscoplastic model for which parameters have been calibrated based on experimental data for a wide range of Grade 91 alloy that has undergone a variety of processing. A Bayesian approach was used to derive distributions of uncertain parameters for this model based on this data set. The second approach is a reduced order model suitable for engineering-scale analysis that is based on the results of a large set of mesoscale simulations. Mesoscale models allow for the microstructure and composition of a particular alloy to be directly taken into account in the computation of the viscoplastic response, but are computationally expensive, which makes it impractical to directly call those models for the material constitutive response in an engineering-scale simulation. The reduced-order representation of the response of the underlying model used here allows for an engineering-scale model to take into account the characteristics of the underlying microstructure, while only incurring a reasonable computational expense. Both of these approaches have different strengths, and are applicable for different parts of the design/analysis process. The phenomenological models can be readily parameterized based on a set of experimental data for a given class of materials and used for scoping calculations. Once a specific material is chosen and adequately characterized, the reduced order models can accurately predict the response of that specific alloy, and because the models are based on predictive models of the underlying microstructure, they can be used to more confidently predict the response under conditions in regions where there is limited experimental data. Both of these models have been integrated in the Grizzly code, which is used here to perform proof-of-concept uncertainty quantification analyses of a simple component under prototypical conditions. The built- in stochastic analysis capabilities in the MOOSE framework that Grizzly is built on are used here to run large sets of simulations for this uncertainty quantification analysis. As would be expected, because the reduced order models are developed for a much more tightly defined alloy, they predict tighter distributions of the time to failure than the phenomenological models, which are calibrated to a broader set of data. Also important is that these simulations demonstrate that a reduced order modeling approach can be successfully deployed to propagate uncertainties from the material scale to practical engineering-scale component simulations.

42 ENGINEERING↗
NASA NTRS1975

Tape tracking and handling for magnetic tape recorders

One of the critical performance and life limiting elements of a spacecraft tape recorder instrumentation system which has received little attention in technical literature is magnetic tape tracking and handling technology. This technology is required to understand how to gently transfer tape from one reel to another with proper alignment and a desirable uniform velocity at the read and write transducer heads. The increased demand for high data rate (i.e., multi-track spacecraft recording instrumentation systems), coupled with performance under extreme environmental conditions, requires a thorough knowledge of the various parameters which establish an optimum designed tape tracking and handling system. Stress analysis techniques are required to evaluate these parameters substantiated with test tape tracking data, to show the effect of each parameter on a tape recorder instrumentation tracking system. The technology is applicable to ground type tape recorders where the detrimental effects of edge guidance can be eliminated.

Paroby, W.↗
NASA NTRS1998

Perspectives on the Future Search for Life on Mars and Beyond

One can view the search for life on Mars in two ways: first, as the initial step in the search for life elsewhere, and second, as the one place where in situ methods for life detection can be tested and proved via sample return. After Mars, most of the life detection will he done via in situ studies with data return. Mars offers us the opportunity to fine tune our methods - perhaps for a long time to come. Our group is involved in the development of methods for life detection that are independent of specific signals used for detection of life on Earth. These approaches include general indicators of metabolic activity and organismal structure and composition. Using such approaches, we hope to detect the signals of life (biosignatures) that are independent of preconceived notions and yet are convincing and unambiguous. The approaches we are focusing on include stable isotopic analyses of metals, mineral formation and disolution, and elemental analysis. These methods allow us to examine samples at a variety of scales, looking for nonequilibrium distribution of elements that serve as biosignatures. For futures studies of Mars and beyond, they, or some variation of them, should allow inference or proof of life in non-Earth locations.

Nealson, K. H.↗
DOE OSTI2026

BLEECAM™ (Benchmarking Life Cycle Environmental, Economic, and Social Metrics for Critical and Advanced Minerals and Materials) [SWR-25-125]

The National Laboratory of the Rockies' (NLR) Benchmarking Life Cycle Environmental, Economic, and Social Metrics for Critical and Advanced Minerals and Materials (BLEECAM™) is an open-source, integrated decision-support tool for evaluating the impacts, risks, and trade-offs across U.S. and global materials supply chains. Funded by the U.S. Department of Energy, BLEECAM supports supply chain and market analysis. The tool integrates multi-objective supply chain optimization, system dynamics, network design, lifecycle assessment, techno-economic modeling, and social impact assessment methods to evaluate how supply chains evolve over time, geography, and deployment scenarios. BLEECAM also supports analysis related to energy infrastructure, data centers and digital infrastructure, advanced manufacturing, and other sectors that depend on critical materials.

Khalifa, SherifA. [National Laboratory of the Rock↗
NASA NTRS1976

Generalized EC&LSS computer program configuration control

The generalized environmental control and life support system (ECLSS) computer program (G189A) simulation of the shuttle orbiter ECLSS was upgraded. The G189A component model configuration was changed to represent the current PV102 and subsequent vehicle ECLSS configurations as defined by baseline ARS and ATCS schematics. The diagrammatic output schematics of the gas, water, and freon loops were also revised to agree with the new ECLSS configuration. The accuracy of the transient analysis was enhanced by incorporating the thermal mass effects of the equipment, structure, and fluid in the ARS gas and water loops and in the ATCS freon loops. The sources of the data used to upgrade the simulation are: (1) ATCS freon loop line sizes and lengths; (2) ARS water loop line sizes and lengths; (3) ARS water loop and ATCS freon loop component and equipment weights; and (4) ARS cabin and avionics bay thermal capacitance and conductance values. A single G189A combination master program library tape was generated which contains all of the master program library versions which were previously maintained on separate tapes. A new component subroutine, PIPETL, was developed and incorporated into the G189A master program library.

Blakely, R. L.↗
NASA NTRS1989

Predicting The Propagation Of Cracks

Advanced Crack Propagation Predictive Analysis Program, FLAGR04, developed as aid in predicting growth of preexisting flaws and cracks in structural components. Provides fracture-mechanics analyst with computerized method of evaluation of "safe crack-growth life" capabilities of structural components. Also used to evaluate tolerance-to-damage aspects of given structural design. Predicts growth of crack by use of two-dimensional model independently predicting growth of flaw in two directions based on calculation of stress-intensity factors. Input to FLAGR04 consists of initial definition of crack, type of rate solution, type and geometry of flaw, properties of material, data on load spectrum, load-stress functions, and design-limit stress levels. Output includes echo of input with any error or warning message and history of propagation of crack. Written in FORTRAN IV.

Tianlai, HU↗
NASA NTRS1993

Meteorological analysis of the November 25 FIRE cirrus-2 case: A well-defined ridge-crest cirrus system over Oklahoma

On the morning of 25 Nov. 1991, a cirrus cloud system formed in a region extending eastward from the continental divide into central Oklahoma and southwestern Kansas. The system moved slowly eastward during the day and maintained a relatively constant scale and shape. From the satellite perspective, this cloud system had a number of morphological similarities to the 27-28 Oct. FIRE (First International Satellite Cloud Climatology Project Regional Experiment) Cirrus-1 case analyzed by Starr and Wylie. By comparison, the present case had much better rawinsonde coverage. The rawinsonde network was much more extensive and the cloud system was relatively slow moving and well-located with respect to the enhanced sounding network and the National Weather Service (NWS) Wind Profiler Network. In addition to the rawinsonde soundings (1200 and 1800 UTC on 25 Nov. and 0000 and 0600 UTC on 26 Nov.) and satellite observations, four aircraft sorties were flown in the northern portion of this cirrus cloud system from mid-morning to mid afternoon. These included microphysical-radiation profiling missions by the NCAR Sabreliner near Tulsa (about midway between COF and OUN) and the NCAR King Air near Ponca City (about 80 km upwind of Tulsa), a microphysical profiling mission by the UND Citation near Tulsa, and a NASA ER-2 overflight. Thus, very good data are available for this case although, unfortunately, the cloud system remained south of the FIRE Hub site at Coffeyville (COF) where extensive ground-based remote sensor was located. The northern edge of the cloud system was visible from COF during most of the day. Given the wealth of available in situ and remote sensing observations, the similarity to the FIRE Cirrus-1 focal case study, and the particularly good match in scale and location of the cloud system with the rawinsonde and profiler networks, analysis of this case may yield very useful results on the life-cycle of this cirrus cloud system. The quality of the meteorological description for this case was assessed based on our preliminary analysis of the rawinsonde observations.

Starr, David↗
NASA NTRSDate not supplied

GL4U: Using Space Biology Omics Data to Provide Bioinformatics Training for Students and Educators

NASA’s GeneLab project provides researchers open access to space-relevant multi-omics data via the Open Science Data Repository (OSDR) that can be mined to understand the effects of spaceflight on biological systems. To maximize the number of scientists who understand and utilize GeneLab data and data processing pipelines, GeneLab created GeneLab for Colleges and Universities (GL4U). GL4U provides space biology-relevant training in bioinformatics to the next generation of scientists through direct (training students) and indirect (training educators) approaches. The GL4U pilot programs were conducted in June 2021 (direct training) and 2022 (indirect training). During the pilots, students and educators at Historically Black Colleges and Universities (HBCUs) and Minority Serving Institutions (MSIs) participated in a week-long (direct training) or two-week-long (indirect training) bootcamp consisting of space biology-specific lectures and hands-on instruction using Jupyter Notebooks to analyze space biology RNA sequencing data from OSDR. During the educator pilot, participants received materials, training, and the necessary compute resources to enable them to run the bootcamp at their home institutions, thereby extending the reach of this initiative. In July 2023, GeneLab is partnering with JPL to expand GL4U to include amplicon sequencing (Amp-Seq) analysis training. During the GL4U Amp-Seq bootcamp, student and educator participants will receive training on how to analyze and interpret Amp-Seq data using the NASA GeneLab data processing pipeline. All bootcamp material, including instructions for requesting compute resources, will be made publicly available on GitHub for educators to teach the GL4U content in subsequent semesters. GL4U provides undergraduate students from underrepresented groups the opportunity to learn about NASA and Space Biology, and to enhance their career prospects by gaining hands-on experience analyzing omics data, a skillset that is highly applicable and marketable in the life sciences. We present results from pre- and post-training surveys completed by all participants of the Amp-Seq bootcamp.

Amanda M Saravia-Butler↗
NASA NTRSDate not supplied

Integrated In-Situ Resource Utilization Modeling of a Lunar Water Processing System

A key element of achieving a sustained surface presence, such as defined in NASA’s Artemis plan, is In-Situ Resource Utilization (ISRU). ISRU is the practice of using local resources to provide mission consumables that reduce system launch mass requirements, and regenerate resources (chiefly, water and oxygen) for propulsion and life support supporting both Lunar and Martian missions. ISRU systems require multiple complex processes, such as excavation, chemical reactors, and electrolysis subsystems that must operate in harmony to optimize the overall system process from beginning to end. The Mission Analysis and Integration Tool (MAIT) connects individual subsystem models into a customized, flexible framework for the purpose of technology downselect, optimization, and end-to-end process planning. MATLAB was favorable to use as the main software integration tool due to its ability to communicate with a vast number of other programming languages and makes up the backbone of data flow between inputs and outputs to the subsystem models. MAIT initially evaluated a suite of technologies, including but not limited to, the water processing Lunar Auger Dryer for ISRU (LADI) system and an oxygen extraction carbothermal reduction process. With individual models consolidated, the MAIT tool generated over 60,000 cases during its parametric sweeps; these system iterations produced valuable insight into the optimal LADI geometry for minimizing heater energy demands, estimating carbothermal reactor and radiator mass relationships, and calculated the power dynamics of the electrolysis unit. Efforts to update the MAIT tool are ongoing to accommodate and scale ISRU technologies supporting the Space Technology Mission Directorate’s (STMD) commercialization strategy, and increase the MAIT software capability to handle a wide array of ISRU system models beyond the Lunar environment, e.g. production of propellant for a Martian lander.

Avery Carlson↗
DOE OSTI2020

Continuous and discrete modeling of HIV-1 decline on therapy

Mathematical models have shed light on the dynamics of HIV- 1 infection in vivo. In this paper, we generalize continuous mathematical models of drug therapy for HIV-1 by Perelson et al. (Science 271:1582–1586, 1996) and Perelson and Nelson (SIAM Rev 41:3–44, 1999) on time scales, i.e., a nonempty closed subset of real numbers in order to derive new discrete models that predict the total concentration of plasma virus as a function of time. Here, one of our main goals is to compare discrete mathematical models with the continuous model in Perelson et al. (1996) where HIV infected patients were given protease inhibitors and sampled frequently thereafter. For the comparison, we use experimental data collected in Perelson et al. (1996) and estimate the parameters such as the virion clearance rate and the rate of loss of infected cells by fitting the total concentration of plasma virus to this data set. Our results show that discrete systems describe the best fit. In the previous models of this study, the efficacy of protease inhibitor is assumed to be perfect. Motivated by Perelson and Nelson (1999), we end the paper with a mathematical model of imperfect protease inhibitor and reverse transcriptase (RT) inhibitor combination therapy of HIV-1 infection on time scales with its stability analysis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

A Comprehensive Investigation of Active Learning Strategies for Conducting Anti-Cancer Drug Screening

It is well-known that cancers of the same histology type can respond differently to a treatment. Thus, computational drug response prediction is of paramount importance for both preclinical drug screening studies and clinical treatment design. To build drug response prediction models, treatment response data need to be generated through screening experiments and used as input to train the prediction models. In this study, we investigate various active learning strategies of selecting experiments to generate response data for the purposes of (1) improving the performance of drug response prediction models built on the data and (2) identifying effective treatments. Here, we focus on constructing drug-specific response prediction models for cancer cell lines. Various approaches have been designed and applied to select cell lines for screening, including a random, greedy, uncertainty, diversity, combination of greedy and uncertainty, sampling-based hybrid, and iteration-based hybrid approach. All of these approaches are evaluated and compared using two criteria: (1) the number of identified hits that are selected experiments validated to be responsive, and (2) the performance of the response prediction model trained on the data of selected experiments. The analysis was conducted for 57 drugs and the results show a significant improvement on identifying hits using active learning approaches compared with the random and greedy sampling method. Active learning approaches also show an improvement on response prediction performance for some of the drugs and analysis runs compared with the greedy sampling method.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2015

The Integrated Medical Model: A Probabilistic Simulation Model Predicting In-Flight Medical Risks

The Integrated Medical Model (IMM) is a probabilistic model that uses simulation to predict mission medical risk. Given a specific mission and crew scenario, medical events are simulated using Monte Carlo methodology to provide estimates of resource utilization, probability of evacuation, probability of loss of crew, and the amount of mission time lost due to illness. Mission and crew scenarios are defined by mission length, extravehicular activity (EVA) schedule, and crew characteristics including: sex, coronary artery calcium score, contacts, dental crowns, history of abdominal surgery, and EVA eligibility. The Integrated Medical Evidence Database (iMED) houses the model inputs for one hundred medical conditions using in-flight, analog, and terrestrial medical data. Inputs include incidence, event durations, resource utilization, and crew functional impairment. Severity of conditions is addressed by defining statistical distributions on the dichotomized best and worst-case scenarios for each condition. The outcome distributions for conditions are bounded by the treatment extremes of the fully treated scenario in which all required resources are available and the untreated scenario in which no required resources are available. Upon occurrence of a simulated medical event, treatment availability is assessed, and outcomes are generated depending on the status of the affected crewmember at the time of onset, including any pre-existing functional impairments or ongoing treatment of concurrent conditions. The main IMM outcomes, including probability of evacuation and loss of crew life, time lost due to medical events, and resource utilization, are useful in informing mission planning decisions. To date, the IMM has been used to assess mission-specific risks with and without certain crewmember characteristics, to determine the impact of eliminating certain resources from the mission medical kit, and to design medical kits that maximally benefit crew health while meeting mass and volume constraints.

Risk Analysis↗
DOE OSTI2022

Dynamic Material Flow Analysis of Silicon Photovoltaic Modules to Support a Circular Economy Transition

Solar photovoltaics (PV) are the fastest growing renewable energy technologies for clean, cheap, and sustainable electricity generation. To prepare for rapid scale-up, the PV industry needs to project material requirements to build out all aspects of the supply chain appropriately and plan to handle large volumes of module waste. Impacts of deploying different material circularity strategies to reduce waste and conserve primary resources need to be quantified to inform sustainable material management. Here, we introduce the photovoltaic dynamic material flow analysis (PV DMFA) model based on PV electricity generation. The model quantifies material flows and stocks in the cradle-to-cradle life cycles of utility-scale c-Si PV systems in the United States through 2100. We present case studies for solar flat glass and aluminum frame materials under various scenarios to project the impacts of PV performance, reliability, and processing parameters, material circularity strategies, and module design shifts. In the absence of circularity measures, ~100 million MT of flat glass and ~12 million MT of aluminum would be needed for PV installations by 2100 to meet projected growth in domestic utility PV demand to nearly 1000 TWh in 2100. With optimistic but feasible improvements in efficiency, reliability, and circularity, material intensity and waste could be reduced by nearly 50%. Efficient module collection, minimally intrusive recycling, and careful scrap handling and cleaning could improve material circularity in the PV value chain. This model serves as a sustainability data support tool that may aid in the circular economy transition for PV systems.

circular economy↗
DOE OSTI2023

Lifetime and Degradation Study of Poly(Methyl Methacrylate) via a Data-Driven Study Protocol Approach

We report to optimize and extend the service life of polymeric materials in outdoor environments, a domain knowledge-based and data-driven approach was utilized to quantitatively investigate the temporal evolution of degradation modes, mechanisms, and rates under various stepwise accelerated exposure conditions. Six formulations of poly(methyl methacrylate) (PMMA) with different combinations of stabilizing additives, including one unstabilized formulation, were exposed in three accelerated weathering conditions. Degradation was dependent on wavelength as samples in UV light at 340 nm (UVA) exposure showed the most yellowing. The unstabilized PMMA formulation showed much higher yellowness index values (59.5) than stabilized PMMA formulations (2–12). Urbach edge analysis shows a shift toward longer wavelength from 285 to 500 nm with increasing exposure time and an increased absorbance around 400 nm of visible region as the unstabilized samples increase in yellowing. The degradation mechanisms of PMMA were tracked using induced absorbance to dose at specific wavelengths that correspond to known degradation mechanisms. The degradation pathway of PMMA was modeled in a framework using network structural equation modeling (netSEM). netSEM showed changes in degradation pathway as PMMA transition stages of degradation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

SPERLU Selective Process for Efficient Removal of Lignin and Upgrading (Final Technical Report)

To meet the growing demand for bio-based chemicals and improve the profitability and efficiency of the emerging biorefinery industry, lignin is an abundant and attractive feedstock. Spero Renewables has developed a proprietary and patent-pending technology, the Selective Process for Efficient Removal of Lignin and Upgrading (SPERLU). The technology is a catalytic deconstruction and upgrading of lignin in lignocellulosic biomass or commercially available technical lignin to produce multi-functional phenol (MFP) products. The SPERLU process has been demonstrated and vetted on a lab scale to convert commercially available technical lignin to MFPs in yields of 60-90% (based on lignin). The MFP products can be separated and further upgraded through catalytic or biological means. Spero performed a detailed kinetic study of the SPERLU process and used the resulting kinetic data to design and construct a mini-pilot-scale reactor for routine production of hundreds of grams of MFP products. Spero’s lignin-based MFPs have been demonstrated for use as a drop-in replacement for bisphenol A (BPA) in the synthesis of thermoset polymers. Spero’s lignin-based thermoset polymers exhibit excellent mechanical properties and can be used in many applications. Additionally, a collaboration with the National Renewable Energy Lab (NREL) was used to evaluate the feasibility of upgrading SPERLU products through biological means into valuable chemicals. A comprehensive technoeconomic analysis (TEA) and Life-cycle analysis (LCA) have been completed and support the case for commercialization of the SPERLU technology. Through this project Spero has significantly de-risked the SPERLU technology and is actively planning larger scale pilot projects.

09 BIOMASS FUELS↗
NASA NTRS1980

Overview of escalator applications in rail transit

The difference in operating environment and in construction between escalators in transit and nontransit use, the impact of recent escalator innovations, and areas which could benefit from urban mass transportation administration sponsored research and development are determined. Several factors causing a more severe transit escalator operating environment are identified. There are no significant design differences between transit and nontransit escalators. Recent innovations that have affected performance and cost include outdoor escalators, extra flat steps at both landings, and modular escalators. Data were collected by interviews at transit agencies. Long term, unscheduled, escalator maintenance records were available for analysis from one property. A description of escalator operating principles is provided. Transit represents less than 5% of the U.S. escalator market. Transit agencies have limited leverage on escalator industry practices. A substantial impact on transit escalator cost and performance can be achieved by research identifying when and how to apply and specify several of the more recent innovations. Purchase of escalators under long term (25 year) maintenance contracts is one method that has been used to promote escalators manufactured for minimum life cycle cost.

Deshpande, G.↗
NASA NTRS1984

Flat-plate module efficiency versus cost tradeoffs

The Five Year Research Plan energy cost methodology and in depth analyses based on the extensive data that are relevant to PV systems are used to facilitate the accomplishment of the $0.15/kWh energy cost goal. An equation is given for the five year energy cost methodology. The allocation guidelines are designed to be consistent with flat solar array (FSA) milestones for module cost, module efficiency, and the programmatic goal for energy cost. They are research targets that appear to be achievable, given prior accomplishments and planned activities in the areas of low cost silicon purification, low cost sheet material, high efficiency cell processing, low cost, long life encapsulants, and automated fabrication method. Extensive sensitivity analysis work has been performed that shows that these guidelines represent an efficient way to meet the intent of the DOE program.

Aster, R. W.↗