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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Spatially Resolved Performance Analysis for Perovskite Solar Cells

This review explores the current state of the art in spatially resolved characterization of mixed-halide perovskite solar cells. As the size of perovskite cells and modules continues to grow, quantification of the spatial distribution of key cell parameters will become increasingly valuable in predicting ultimate cell-level performance and tracking process homogeneity. Here, both high resolution microscopic approaches using scanning techniques and camera-based methods for full-area cell and/or module analysis are discussed. The value of this local data in predicting performance losses at the cell level is particularly emphasized. Measurable physical parameters sensitive to losses of voltage, current, fill factor, and efficiency are discussed together with selected experimental results. It is demonstrated that a combination of spatially resolved cell parameter mapping/imaging can be used to quantitatively discriminate various loss contributions at high resolution. The impact and control of inhomogeneities become particularly important when upscaling from small devices to large formats compatible with industrial mass production.

14 SOLAR ENERGY↗
NASA NTRS2023

Additive Manufacturing Process Development DOE for NASA HR-1 using Laser Blown Powder Directed Energy Deposition

NASA HR-1 is a Fe-Ni-Cr alloy that is used for high pressure hydrogen applications such as rocket engines, energy, and oil and gas. This investigation was focused on conducting a design of experiment program aimed at mapping the parameter process window for NASA HR-1 using the laser blown powder directed energy deposition (LP-DED) process. A two phased design of experiments (DOE), the first phase of the experiment was focused on optimizing single bead tracks while the second phase of the experiment was focused on optimizing bead overlap hatching in a multi pass bead build up. During the first phase of the deposition parameters, namely laser power, travel speed, and powder feed rate were varied. A down selection from the single bead parameter set was made and hatching experiments were conducted that focused on the overlap distance. In this paper the approach for conducting the DOE and results are discussed. The results focused on measurement of bead geometry, the as-built microstructural evolution, and porosity within the samples. The team at MSFC saw a variety of results across the process map created during the first phase of experimentation and were able to down select a parameter that created an optimal bead shape with a minimal amount of build porosity. It was determined that laser power and robot travel speed were the most sensitive parameters. The results from this investigation will inform future laser powder directed energy deposition parameter developments.

Parker Shake↗
NASA NTRS1994

Efficient Updating of Model Parameters Using Modal Coordinates

Model correlation methods based on iterative modification of physical model parameters have been used with frequent success. The cost and time to perform these methods is driven mostly by the need to recompute normal modes and parameter sensitivities from the full finite element model after each adjustment.

modal↗
DOE OSTI2022

Induced seismicity potential based on probabilistic geomechanics for the San Juan Basin CarbonSAFE project

Although geologic carbon sequestration projects have yet to induce — or may never induce — a damaging earthquake, experiences from other deep injection industries such as hydraulic fracturing, enhanced geothermal systems, and saltwater disposal suggest that effective quantitative seismic risk assessment is necessary for deep saline carbon capture and sequestration (CCS) projects. One such imminent CCS project is the San Juan Basin CarbonSAFE Phase III program. We use Monte Carlo probabilistic geomechanical analyses combined with observations of the geologic and operational parameters of the San Juan Basin site and suggest that this project is of low-induced seismic risk. The primary analysis is split into four sections. First, we assess the literature for faults and past seismicity, and at least five faulting scenarios are directly relevant. Second, we develop and calibrate an integrated earth model for the project site. Third, we perform Monte Carlo simulations that consider reasonable uncertainties of the geomechanical parameters. Of five tested faulting scenarios, only one presents high Coulomb failure functions, but fourth, we determine the risk to be low based on the combined lack of historical seismicity, the geologic framework of the faulting scenario, and the presence of saltwater injection at the same depth as the proposed supercritical carbon dioxide injection. The most sensitive parameters in the geomechanical calculations are the fault dip and the coefficient of friction. The least sensitive are the fault strike and the orientation of the maximum horizontal principal stress.

58 GEOSCIENCES↗
DOE OSTI2019

Robust Time-Varying Parameter Identification for Composite Load Modeling

With the increasing integration of uncertain resources, e.g., renewables, electric vehicles, and demand responses, it is imperative to understand the characteristics of loads for power system analysis and control. Challenges of load modeling come from a variety of load components and time-varying compositions. In addition, the existence of outliers in measurements further complicates the problem. This paper proposes a robust time-varying parameter identification technique for composite ZIP and induction motor load models. A batch-model regression form, including time-varying parameters, is established based on state transition models and observation models with current observations and previous predictions to guarantee data redundancy. To deal with outliers, down-weighting coefficients of measurements are calculated with a projection statistics approach. Based on the batch-model regression and the down-weighting coefficients, parameter identification at each sample time is formulated as a weighted least squares optimization, which is solved by the Newton-Raphson approach with the previous estimated parameters as the initial iteration values. In addition, parameters' sensitivities to different outliers in measurements are analyzed. Results on the IEEE 57-bus system and IEEE 118-bus system show that the proposed algorithm can robustly identify time-varying parameters for the composite load models.

Composite load model↗
DOE OSTI2022

Rate-Dependent Dynamic Cylindrical Cavity Expansion Equations for Conical- and Ogival-Nosed Projectiles

The dynamic cylindrical cavity expansion of rate-dependent materials was previously derived by Warren to examine the effects of strain-rate sensitivity on the radial stress acting on a perforating projectile. However, the equations presented were largely analytical and were not further applied to predict the ballistic performance of ductile target plates. The current work expands on Warren’s derivation to model the dynamics of conical and ogival geometries, and the rate-dependent model is compared to prior experimental results of 7.62-mm APM2 rounds impacting 6061-T6511 aluminum alloy plates. The results show that including rate effects improves the ballistic performance prediction, even for a marginally strain-rate sensitive material such as Al6061-T651. However, existing semi-empirical variations of the cavity expansion model can provide the same degree of accuracy if target material rate-sensitivity parameters are not readily available.

36 MATERIALS SCIENCE↗
NASA NTRS1987

The effects of stimulated star formation on the evolution of the galaxy. III - The chemical evolution of nonlinear systems

The evolution of models for star formation in galaxies with disk and halo components is discussed. Two phases for the halo (gas and stars) and three for the disk (including clouds) are used in these calculations. The star-formation history is followed using nonlinear phase-coupling models which completely determine the populations of the phases as a function of time. It is shown that for a wide range of parameters, including the effects of both spontaneous and stimulated star formation and mass exchange between the spatial components of the system, the observed chemical history of the galaxy can easily be obtained. The most sensitive parameter in the detailed metallicity and star-formation history for the system is the rate of return of gas to the diffuse phase upon stellar death.

Shore, Steven N.↗
NASA NTRS2012

Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact Scenarios

Two full-scale crash tests of an MD-500 helicopter were conducted in 2009 and 2010 at NASA Langley's Landing and Impact Research Facility in support of NASA s Subsonic Rotary Wing Crashworthiness Project. The first crash test was conducted to evaluate the performance of an externally mounted composite deployable energy absorber (DEA) under combined impact conditions. In the second crash test, the energy absorber was removed to establish baseline loads that are regarded as severe but survivable. The presence of this energy absorbing device reduced the peak impact acceleration levels by a factor of three. Accelerations and kinematic data collected from the crash tests were compared to a system-integrated finite element model of the test article developed in parallel with the test program. In preparation for the full-scale crash test, a series of sub-scale and MD-500 mass simulator tests were conducted to evaluate the impact performances of various components and subsystems, including new crush tubes and the DEA blocks. Parameters defined for the system-integrated finite element model were determined from these tests. Results from 19 accelerometers placed throughout the airframe were compared to finite element model responses. The model developed for the purposes of predicting acceleration responses from the first crash test was inadequate when evaluating more severe conditions seen in the second crash test. A newly developed model calibration approach that includes uncertainty estimation, parameter sensitivity, impact shape orthogonality, and numerical optimization was used to calibrate model results for the full-scale crash test without the DEA. This combination of heuristic and quantitative methods identified modeling deficiencies, evaluated parameter importance, and proposed required model changes. The multidimensional calibration techniques presented here are particularly effective in identifying model adequacy. Acceleration results for the calibrated model were compared to test results and the original model results. There was a noticeable improvement in the pilot and copilot region, a slight improvement in the occupant model response, and an over-stiffening effect in the passenger region. One lesson learned was that this approach should be adopted early on, in combination with the building-block approaches that are customarily used, for model development and pretest predictions. Complete crash simulations with validated finite element models can be used to satisfy crash certification requirements, potentially reducing overall development costs.

Annett, Martin S.↗
NASA NTRS2012

Calibration of Airframe and Occupant Models for Two Full-Scale Rotorcraft Crash Tests

Two full-scale crash tests of an MD-500 helicopter were conducted in 2009 and 2010 at NASA Langley's Landing and Impact Research Facility in support of NASA s Subsonic Rotary Wing Crashworthiness Project. The first crash test was conducted to evaluate the performance of an externally mounted composite deployable energy absorber under combined impact conditions. In the second crash test, the energy absorber was removed to establish baseline loads that are regarded as severe but survivable. Accelerations and kinematic data collected from the crash tests were compared to a system integrated finite element model of the test article. Results from 19 accelerometers placed throughout the airframe were compared to finite element model responses. The model developed for the purposes of predicting acceleration responses from the first crash test was inadequate when evaluating more severe conditions seen in the second crash test. A newly developed model calibration approach that includes uncertainty estimation, parameter sensitivity, impact shape orthogonality, and numerical optimization was used to calibrate model results for the second full-scale crash test. This combination of heuristic and quantitative methods was used to identify modeling deficiencies, evaluate parameter importance, and propose required model changes. It is shown that the multi-dimensional calibration techniques presented here are particularly effective in identifying model adequacy. Acceleration results for the calibrated model were compared to test results and the original model results. There was a noticeable improvement in the pilot and co-pilot region, a slight improvement in the occupant model response, and an over-stiffening effect in the passenger region. This approach should be adopted early on, in combination with the building-block approaches that are customarily used, for model development and test planning guidance. Complete crash simulations with validated finite element models can be used to satisfy crash certification requirements, thereby reducing overall development costs.

Annett, Martin S.↗
DOE OSTI2024

Crack opening calculation in phase-field modeling of fluid-filled fracture: A robust and efficient strain-based method

The phase-field method has become popular for the numerical modeling of fluid-filled fractures, thanks to its ability to represent complex fracture geometry without algorithms. However, the algorithm-free representation of fracture geometry poses a significant challenge in calculating the crack opening (aperture) of phase-field fracture, which governs the fracture permeability and hence the overall hydromechanical behavior. Although several approaches have been devised to compute the crack opening of phase-field fracture, they require a sophisticated algorithm for post-processing the phase-field values or an additional parameter sensitive to the element size and alignment. Here, we develop a novel method for calculating the crack opening of fluid-filled phase-field fracture, which enables one to obtain the crack opening without additional algorithms or parameters. Here we transform the displacement-jump-based kinematics of a fracture into a continuous strain-based version, insert it into a force balance equation on the fracture, and apply the phase-field approximation. Through this procedure, we obtain a simple equation for the crack opening which can be calculated with quantities at individual material points. We verify the proposed method with analytical and numerical solutions obtained based on discrete representations of fractures, demonstrating its capability to calculate the crack opening regardless of the element size or alignment.

58 GEOSCIENCES↗
NASA NTRS1986

Evaluation and Improvement of Liquid Propellant Rocket Chugging Analysis Techniques. Part 1: A One-Dimensional Analysis of Low Frequency Combustion Instability in the Fuel Preburner of the Space Shuttle Main Engine

Low frequency combustion instability, known as chugging, is consistently experienced during shutdown in the fuel and oxidizer preburners of the Space Shuttle Main Engines. Such problems always occur during the helium purge of the residual oxidizer from the preburner manifolds during the shutdown sequence. Possible causes and triggering mechanisms are analyzed and details in modeling the fuel preburner chug are presented. A linearized chugging model, based on the foundation of previous models, capable of predicting the chug occurrence is discussed and the predicted results are presented and compared to experimental work performed by NASA. Sensitivity parameters such as chamber pressure, fuel and oxidizer temperatures, and the effective bulk modulus of the liquid oxidizer are considered in analyzing the fuel preburner chug. The computer program CHUGTEST is utilized to generate the stability boundary for each sensitivity study and the region for stable operation is identified.

Lim, Kair Chuan↗
NASA NTRS1995

A Method Based on Radiative Cooling for Detecting Structural Changes in Undercooled Metallic Liquids

We introduce a structure-sensitive parameter for undercooled melts which can be measured in containerless processing experiments. We have established that the ratio, R(T), of hemispherical total emissivity epsilon(sub T)(T) to constant-pressure specific heat c(sub p)(T) can serve as an indicator which is sensitive to any changes in short range atomic order in undercooled metallic melts. R(T) (triple bonds) epsilon(sub T)(T)/c(sub p)(T) values for nickel, zirconium, and silicon have been obtained using the high temperature electrostatic levitator while the levitated melts were undergoing purely radiative cooling into the deeply undercooled region. R(T) plots for undercooled liquid nickel and zirconium indicate no significant change in short-range structure from their melting temperatures to 15% undercooling. In contrast, liquid silicon shows marked short-range structural changes beginning above its melting temperature and extending throughout the undercooled region. The short-range structure of liquid silicon is related to the highly-directional covalent bonding which characterizes its solid form. The nickel and zirconium data show that epsilon(sub T) varies linearly with T, in support of metal emissivity theories.

Rulison, Aaron J.↗
NASA NTRSDate not supplied

Methodology Report of Cost Benefit Analysis of Space Based Solar Power

Space-based solar power (SBSP) is the concept of gathering power in space and transmitting it wirelessly to users on Earth or elsewhere in space. SBSP has seen renewed interest from governments, businesses, and universities for reasons including persistent operations in space, achieving carbon neutrality targets, and more. Several major government agencies in Europe, Asia, and the Americas have renewed their SBSP investigations, and hundreds of millions of dollars have been donated to universities to advance the technical state of the art. Given the renewed interest, this study will identify and update some key system parameters to current performance levels. This paper presents the methodology and approach to identify the fiscal and environmental costs and benefits of SBSP when compared to other sustainable and grid-scale energy sources. From these divergent angles the models evaluate fiscal and environmental impacts, identify the state of the most sensitive parameters of the designs, and seek to provide context to leadership on the relative value of pursuing SBSP related technologies.

Space-based solar power↗
NASA NTRS1982

Computer-aided prediction of high-frequency performance limits in silicon bipolar integrated circuits

A circuit model for an existing silicon integrated bipolar junction transistor (IBJT) is used to evaluate presently achievable high frequency circuit performance. The relationship between circuit model and processing parameters are semi-quantitatively explored to make predictions on the frequency response, which can be achieved through realistic device fabrication modifications. A new figure of merit is introduced, which is defined as the signal frequency at which an integrated bipolar junction transistor can deliver a power gain of G. The most sensitive parameter influencing attainable high frequency IBJT performance is base resistance.

Burns, J. L.↗
DOE OSTI2024

Projective Integral Updates for High-Dimensional Variational Inference

Variational inference is an approximation framework for Bayesian inference that seeks to improve quantified uncertainty in predictions by optimizing a simplified distribution over parameters to stand in for the full posterior. Capturing model variations that remain consistent with training data enables more robust predictions by reducing parameter sensitivity. This work introduces a fixed-point optimization for variational inference that is applicable when every feasible log density can be expressed as a linear combination of functions from a given basis. In such cases, the optimizer becomes a fixed-point of projective integral updates. When the basis spans univariate quadratics in each parameter, the feasible distributions are Gaussian mean-fields and the projective integral updates yield quasi-Newton variational Bayes (QNVB). Other bases and updates are also possible. Since these updates require high-dimensional integration, this work begins by proposing an efficient quasirandom sequence of quadratures for mean-field distributions. Each iterate of the sequence contains two evaluation points that combine to correctly integrate all univariate quadratic functions and, if the mean-field factors are symmetric, all univariate cubics. More importantly, averaging results over short subsequences achieves periodic exactness on a much larger space of multivariate polynomials of quadratic total degree. The corresponding variational updates require four loss evaluations with standard (not second-order) backpropagation to eliminate error terms from over half of all multivariate quadratic basis functions. Furthermore, this integration technique is motivated by first proposing stochastic blocked mean-field quadratures, which may be useful in other contexts. A PyTorch implementation of QNVB allows for better control over model uncertainty during training than competing methods. Experiments demonstrate superior generalizability for multiple learning problems and architectures.

Gaussian mean-field↗
DOE OSTI2020

Validation and Sensitivity Analysis of a 1-D Lake Model Across Global Lakes

Lakes have important influence on weather and climate from local to global scales. However, their prediction using numerical models is notoriously difficult because lakes are highly heterogeneous across the globe, but observations are sparse. In this study, we assessed the performance of a 1-D lake model in simulating the thermal structures of 58 lakes with diverse morphometric and geographic characteristics by following the phase 2a local lake protocol of the Inter-sectoral Impact Model Intercomparison Project (ISIMIP2a). After calibration, the root-mean-square errors (RMSE) were below 2 °C for 70% and 75% of the lakes for epilimnion and full-profile temperature simulations, with an average of 1.71 °C and 1.43 °C, respectively. The model performance mainly depended on lake shape rather than location, supporting the possibility of grouping model parameters by lake shape for global applications. Furthermore, through machine-learning based parameter sensitivity tests, we identified turbulent heat fluxes, wind-driven mixing and water transparency as the major processes controlling lake thermal and mixing regimes. Snow density was also important for modeling the ice phenology of high-latitude lakes. The relative influence of the key processes and the corresponding parameters mainly depended on lake latitude and depth. Turbulent heat fluxes showed a decreasing importance in affecting epilimnion temperature with increasing latitude. Wind-driven mixing was less influential to lake stratification for deeper lakes while the impact of light extinction, on the contrary, showed a positive correlation with depth. Our findings may guide improvements in 1-D lake model parameterizations to achieve higher fidelity in simulating global lake thermal dynamics.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Assisting Public Organizations in Their Outsourcing Endeavors: A Decision Support Mode

There has been a tremendous growth in outsourcing practices in recent years. The public organizations in the United States have outsourced some functions and are now being compelled to outsource additional ones. While there are numerous studies that document and analyze outsourcing practices, there is limited research to guide public or governmental organizations in determining what functions to outsource. This study fills this gap by developing a decision support model for a typical public organization in determining what to outsource and how. A set of outsourcing decision factors is identified that can be used as parameters in the three integer programming formulations developed. These formulations are used as solution engines in the model. The first formulation identifies which functions are the best candidates for outsourcing given the organization's priorities. The other formulations place the functions into recommended contracts and re-assign displaced employees. Data from NASA Glenn Research Center in Ohio is used to test and analyze the model. Analysis indicates that cost and skills-related factors are the most sensitive parameters for the data tested. The model and the formulations are a relatively comprehensive package and may help guide outsourcing decisionmakers and policymakers in public organizations.

Kremic, TIbor↗