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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Y-12 Nuclear Criticality Safety Program Health Model: Development, Use and Benefits

The Y-12 National Security Complex (Y-12) operates seven diverse enriched uranium processing facilities and maintains a comprehensive nuclear criticality safety (NCS) program. Given the magnitude of the hazard, the NCS program receives significant oversight. Describing the scope and health of the Y-12 NCS program to sometimes non-expert stakeholders with limited time had historically focused on recent events and “hot topics” which did not always convey sufficient context (i.e., how to differentiate between an individual performance issue and a systemic concern). Y-12 created the NCS Program Health (NCSPH) Model to provide a complete and holistic framework to quantify and communicate NCS program health. The model is constructed in a tiered fashion with the top tier broken into three (3) Tier 2 elements, fourteen (14) Tier 3 elements, and 104 Tier 4 and 5 elements. This granularity ensures every feature of the NCS Program is accounted for and stakeholders can see how these features support the collective whole. The model is used as the framework for NCS communications including program plans, reports, health surveys, and meeting agendas. The model has substantially improved stakeholder appreciation for the entirety of the NCS program and how events and assessment results factor into an overarching conclusion on NCS program health. While some details are Y-12 specific, the NCSPH model can easily be tailored for any other site with an NCS program.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2008

Progress of 2-micron Detectors for Application to Lidar Remote Sensing

AlGaAsSb/InGaAsSb heterojunction phototransistors were developed at Astropower, Inc under Laser Risk Reduction Program (LRRP) for operation in the 2-micron region. These phototransistors were optimized for 2-micron detection and have high quantum efficiency (>60%), high gain (>10(exp 3)) and low noise-equivalent- power (<5x10(exp -14) W/Hz), while operating at low bias voltage. One of these phototransistors was tested in lidar mode using the 2-micron CO2 Differential Absorption Lidar (DIAL) system currently under development under the Instrument Incubator Program (IIP) at NASA Langley. Lidar measurements included detecting atmospheric structures consisting of thin clouds in the mid-altitude and near-field boundary layer. These test results are very promising for the application of phototransistors for the two-micron lidar remote sensing. In addition, HgCdTe avalanche photodiodes (APD) acquired from Raytheon were used in atmospheric testing at 2-microns. A discussion of these measurements is also presented in this paper.

Abedin, M. N.↗
DOE OSTI2018

Translational Systems Pharmacology‐Based Predictive Assessment of Drug‐Induced Cardiomyopathy

Drug‐induced cardiomyopathy contributes to drug attrition. We compared two pipelines of predictive modeling: (1) applying elastic net (EN) to differentially expressed genes (DEGs) of drugs; (2) applying integer linear programming (ILP) to construct each drug's signaling pathway starting from its targets to downstream proteins, to transcription factors, and to its DEGs in human cardiomyocytes, and then subjecting the genes/proteins in the drugs' signaling networks to EN regression. We classified 31 drugs with availability of DEGs into 13 toxic and 18 nontoxic drugs based on a clinical cardiomyopathy incidence cutoff of 0.1%. The ILP‐augmented modeling increased prediction accuracy from 79% to 88% (sensitivity: 88%; specificity: 89%) under leave‐one‐out cross validation. The ILP‐constructed signaling networks of drugs were better predictors than DEGs. Per literature, the microRNAs that reportedly regulate expression of our six top predictors are of diagnostic value for natural heart failure or doxorubicin‐induced cardiomyopathy. This translational predictive modeling might uncover potential biomarkers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Unique phase identification of trimetallic copper iron manganese oxygen carrier using simultaneous differential scanning calorimetry/thermogravimetric analysis during chemical looping combustion reactions with methane

Chemical looping combustion (CLC) is a promising combustion technology that generates heat and sequestration-ready carbon dioxide that is undiluted by nitrogen from the combustion of carbonaceous fuels with an oxygen carrier, or metal oxide. This process is highly dependent on the reactivity and stability of the oxygen carrier. The development of oxygen carriers remains one of the major barriers for commercialization of CLC. Synthetic oxygen carriers, consisting of multiple metal components, have demonstrated enhanced performance and improved CLC operation compared to single metal oxides. However, identification of the complex mixed metal oxide phases that form after calcination or during CLC reactions has been challenging. Without an understanding of the dominant metal oxide phase, it is difficult to determine reaction parameters and the oxygen carrier reduction pathway, which are necessary for CLC reactor design. This is particularly challenging for complex multi-component oxygen carriers such as copper iron manganese oxide (CuFeMnO 4 ). This study aims to differentiate the unique phase formation of a highly reactive, complex trimetallic oxygen carrier, CuFeMnO 4 , from its single and bimetallic counterparts using thermochemical and reaction data obtained from simultaneous differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) during temperature programmed reductions (TPR) with methane. DSC/TGA experiments during TPR with methane provides heat flow data and corresponding reaction rate data that can be used to determine reaction routes and mechanisms during methane reduction. Furthermore, non-isothermal TPR data provides the advantage of distinguishing reactions that may not be observable in isothermal analysis. The detailed thermochemical and reaction data, obtained during TPR with methane, distinguished a unique reduction pathway for CuFeMnO 4 that differed from its single and bimetallic counterparts. This is remarkable since X-ray diffraction (XRD) data alone could not be used to distinguish the reactive trimetallic oxide phase due to overlapping peaks from various single and mixed metal oxides. The unique reduction pathway of CuFeMnO 4 was further characterized in this study using in-situ XRD TPR with methane to determine changes in the dominant trimetallic phase that influenced the thermochemical and reaction rate data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Poisson_CCD: A dedicated simulator for modeling CCDs

A dedicated simulator, Poisson_CCD, has been constructed which models astronomical CCDs by solving Poisson’s equation numerically and simulating charge transport within the CCD. The potentials and free carrier densities within the CCD are self-consistently solved for, giving realistic results for the charge distribution within the CCD storage wells. The simulator has been used to model the CCDs that are being used to construct the LSST digital camera. The simulator output has been validated by comparing its predictions with several different types of CCD measurements, including astrometric shifts, brighter-fatter induced pixel–pixel covariances, saturation effects, and diffusion spreading. The code is open source and freely available.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

An Analysis of the Sensitivity of Proteogenomic Mapping of Somatic Mutations and Novel Splicing Events in Cancer

Improvements in mass spectrometry (MS)-based peptide sequencing provide a new opportunity to determine whether polymorphisms, mutations and splice variants identified in cancer cells are translated. Herein we therefore describe a proteogenomic data integration tool (QUILTS) and illustrate its application to whole genome, transcriptome and global MS peptide sequence datasets generated from a pair of luminal and basal-like breast cancer patient derived xenografts (PDX). The sensitivity of proteogenomic analysis for singe nucleotide variant (SNV) expression and novel splice junction (NSJ) detection was probed using multiple MS/MS process replicates. Despite over thirty sample replicates, only about 10% of all SNV (somatic and germline) were detected by both DNA and RNA sequencing were observed as peptides. An even smaller proportion of peptides corresponding to NSJ observed by RNA sequencing were detected (<0.1%). Peptides mapping to DNA-detected SNV without a detectable mRNA transcript were also observed demonstrating the transcriptome coverage was also incomplete (~80%). In contrast to germ-line variants, somatic variants were less likely to be detected at the peptide level in the basal-like tumor than the luminal tumor raising the possibility of differential translation or protein degradation effects. In conclusion, the QUILTS program integrates DNA, RNA and peptide sequencing to assess the degree to which somatic mutations are translated and therefore biologically active. By identifying gaps in sequence coverage QUILTS benchmarks current technology and assesses progress towards whole cancer proteome and transcriptome analysis.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2025

FSEN Reaction Rate Calculations in MCNP [Slides]

FSEN provides an opportunity to quickly calculate sensitivities to orthogonal measurements during integral experiments. Toy problem has been deployed to expand on verification of FSEN for reaction rate ratios. While there is decent agreement, further investigation must be done on multiplication’s impact on sensitivity vector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

CRISPR/Cas9 Directed Reprogramming of iPSC for Accelerated Motor Neuron Differentiation Leads to Dysregulation of Neuronal Fate Patterning and Function

Neurodegeneration causes a significant disease burden and there are few therapeutic interventions available for reversing or slowing the disease progression. Induced pluripotent stem cells (iPSCs) hold significant potential since they are sourced from adult tissue and have the capacity to be differentiated into numerous cell lineages, including motor neurons. This differentiation process traditionally relies on cell lineage patterning factors to be supplied in the differentiation media. Genetic engineering of iPSC with the introduction of recombinant master regulators of motor neuron (MN) differentiation has the potential to shorten and streamline cell developmental programs. We have established stable iPSC cell lines with transient induction of exogenous LHX3 and ISL1 from the Tet-activator regulatory region and have demonstrated that induction of the transgenes is not sufficient for the development of mature MNs in the absence of neuron patterning factors. Comparative global transcriptome analysis of MN development from native and Lhx-ISL1 modified iPSC cultures demonstrated that the genetic manipulation helped to streamline the neuronal patterning process. However, leaky gene expression of the exogenous MN master regulators in iPSC resulted in the premature activation of genetic pathways characteristic of the mature MN function. Dysregulation of metabolic and regulatory pathways within the developmental process affected the MN electrophysiological responses.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1972

The influence of polarization on millimeter wave propagation through rain

A program for the measurement and analysis of the depolarization and differential attenuation that occur when millimeter wave signals propagate through rain is described. Initial data are taken along a 1.43 km path at 17.65 GHz and a supporting theoretical model is developed to relate the propagation effects to rainfall rate and wind velocity. A block diagram of the overall experiment is included. It consists of: (1) an RF system (millimeter wave transmitter and receiver), (2) transmitting and receiving antennas, (3) a weather system with rain gauges, wind sensors, and drop counters, and (4) a digital control, processing, and data storage system.

Bostian, C. W.↗
NASA NTRS1979

Analytical modeling of flash-back phenomena

To understand the flame flash-back phenomena more extensively, an analytical model was formed and a numerical program was written and tested to solve the set of differential equations describing the model. Results show that under a given set of conditions flame propagates in the boundary layer on a flat plate when the free stream is at or below 1.8 m/s.

Feng, C. C.↗
NASA NTRS1980

Thrust-vectored differential turns

Barrier surface construction in the joint space of the differential turning game for thrust-vectored vs. conventional aircraft is discussed. Differential-turn studies are based on modifications of existing computer programs including an energy-turn program, and one which generates hodograph data. Optimal turning flight in energy approximation is discussed for the conventional aircraft configurations. It is concluded that any advantages realized from thrust-vectoring are minor, unless hover is possible, where advantages would be major at low energies, and affect tactics at high energies as well.

Kelley, H. J.↗
NASA NTRS1987

Simulation of AFC for a DMSK Receiver

Low bit rates suitable for low-cost satellite communications. LOOP computer program written to simulate automatic frequency control (AFC) subsystem of differential minimum-shift keying (DMSK) receiver with bit rate of 2,400 baud. AFC simulated by LOOP is first-order loop configuration with first-order resistance-and-capacitance filter. Written in MS SuperSoft FORTRAN 77.

Davarian, Faramaz↗
NASA NTRS1989

Path-Following Solutions Of Nonlinear Equations

Report describes some path-following techniques for solution of nonlinear equations and compares with other methods. Use of multipurpose techniques applicable at more than one stage of path-following computation results in system relatively simple to understand, program, and use. Comparison of techniques with method of parametric differentiation (MPD) reveals definite advantages for path-following methods. Emphasis in investigation on multiuse techniques being applied at more than one stage of path-following computation. Incorporation of multipurpose techniques results in concise computer code relatively simple to use.

Barger, Raymond L.↗
NASA NTRS1992

Automatic differentiation as a tool in engineering design

Automatic Differentiation (AD) is a tool that systematically implements the chain rule of differentiation to obtain the derivatives of functions calculated by computer programs. AD is assessed as a tool for engineering design. The forward and reverse modes of AD, their computing requirements, as well as approaches to implementing AD are discussed. The application of two different tools to two medium-size structural analysis problems to generate sensitivity information typically necessary in an optimization or design situation is also discussed. The observation is made that AD is to be preferred to finite differencing in most cases, as long as sufficient computer storage is available; in some instances, AD may be the alternative to consider in lieu of analytical sensitivity analysis.

Barthelemy, Jean-Francois↗
NASA NTRS1992

Automatic Differentiation as a tool in engineering design

Automatic Differentiation (AD) is a tool that systematically implements the chain rule of differentiation to obtain the derivatives of functions calculated by computer programs. In this paper, it is assessed as a tool for engineering design. The paper discusses the forward and reverse modes of AD, their computing requirements, and approaches to implementing AD. It continues with application to two different tools to two medium-size structural analysis problems to generate sensitivity information typically necessary in an optimization or design situation. The paper concludes with the observation that AD is to be preferred to finite differencing in most cases, as long as sufficient computer storage is available.

Barthelemy, Jean-Francois M.↗
NASA NTRS2006

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

Rai, Man Mohan↗