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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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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Robust Parameter Design on Dual Stochastic Response Models With Constrained Bayesian Optimization

In engineering system design, minimizing the variations of the quality measurements while guaranteeing their overall quality up to certain levels, namely the robust parameter design (RPD), is crucial. Recent works have dealt with the design of a system whose response-control variables relationship is a deterministic function with a complex shape and function evaluation is expensive. In this work, we propose a Bayesian optimization method for the RPD of stochastic functions. Dual stochastic response models are carefully designed for stochastic functions. The heterogeneous variance of the sample mean is addressed by the predictive mean of the log variance surrogate model in a two-step approach. We establish an acquisition function that favors exploration across the feasible and optimality-improvable regions to effectively and efficiently solve the stochastic constrained optimization problem. Further, the performance of our proposed method is demonstrated by the extensive numerical and case studies. Note to Practitioners-Many manufacturing processes involve undesirable variations, which create variations in the final products. For example, many emerging manufacturing processes, such as nanomanufacturing, involve complex physical and chemical dynamics and transformation, creating variations in the manufacturing output. In such processes, it is crucial to design the manufacturing processes or products so that they have minimum variations in their quality. Meanwhile, it is also important to maintain the overall quality of the designed processes or products. Furthermore, acquiring data from many advanced manufacturing processes is often very costly, especially in the designing stage. In this work, we propose a data-driven method that automatically finds the best setting of manufacturing processes or products with the minimum variations of quality and a given constraint on the average quality satisfied. Our proposed method is used before conducting every experiment; It analyzes the historical data from previous experiments and provides a setting to be used in the next experiment. Our proposed method efficiently utilizes the historical data, and thus finds the best robust setting by conducting only a small number of experiments.

42 ENGINEERING↗

DOE OSTI2025

Benefits of Dual Fuel Heat Pump Grid-responsive Control: A Model-based Control Optimization Approach Using Building and Equipment Co-simulation

Conventional dual fuel heat pumps lack the intelligent control mechanisms to efficiently manage the switch between heat pump and furnace, leading to sub-optimal energy usage and, in some cases, increased operating costs. To resolve this gap, this study applies optimized control on hybrid heat pumps. With a focus on equipment control strategies, we compare the performances of five spacing heating equipment, including a conventional heat pump (HP), a conventional furnace, a dual fuel heat pump (DFHP) with conventional control, a dual fuel heat pump with smart control, and a novel seamlessly fuel flexible heat pump (SFFHP). While DFHP runs on either gas or electricity at any given moment, SFFHP concurrently consumes gas and electricity by continuously optimizing the proportion of each. In this research, a co-simulation framework is developed by integrating a building envelope model with a physics-based heat pump simulation model to analyze the benefits of grid-responsive controls of DFHP and SFFHP. The model-based optimal controls adjust the operation of the heat pump and gas furnace based on utility price signals and marginal grid emission to minimize utility cost and CO 2 emissions for multiple climate zones, different utility tariffs, and marginal grid emission scenarios. Case studies in Chicago and Los Angeles demonstrate that SFFHP and DFHP, with model-based optimal control, can deliver significant reductions in peak demand, utility cost, and CO 2 emission. In Chicago, SFFHP and smart controlled DFHP yield up to 64.7% and 61.7% utility cost reduction and up to 15.7% and 8.5% CO 2 emission reduction compared to the gas furnace. In Los Angeles, SFFHP and smart controlled DFHP achieve up to 43.6% and 40.1% utility cost reduction and up to 13.8% and 14.1% CO2 emission reduction compared to conventional heat pumps. In conclusion, by leveraging the fuel flexibility nature of dual fuel heat pumps, the model-based control optimization approach makes dual fuel heat pump an attractive option for demand response programs.

Control↗

NASA NTRS1991

The zeroes of controlled structures - Sensor/actuator attributes and structural modelling

The effects of sensor/actuator design and modeling decisions on the zero frequencies of single input single output structural systems are explored. A zero definition based on the high gain closed loop character of the poles of a system is used to study parametrically zeroes as a function of sensor and actuator location. An infinite order model is adopted so that the effects of finite order modeling are removed. Examples focus on point or localized actuators and sensors and simple uniform structures. The sensitivity of the zero frequencies to changes in the sensor and actuator location for both collocated and non-collocated cases are presented. Non-minimum phase behavior is visible in only certain non-collocated situations. In addition to the sensor/actuator attributes, the zeroes are shown to be a function of the truncation and discretization used to model the structural response for collocated and dual systems. Methods for improving the zero predictions in the control bandwidth are suggested.

Fleming, Farla M.↗

NASA NTRS2011

Dual Heat Pulse, Dual Layer Thermal Protection System Sizing Analysis and Trade Studies for Human Mars Entry Descent and Landing

NASA has been recently updating design reference missions for the human exploration of Mars and evaluating the technology investments required to do so. The first of these started in January 2007 and developed the Mars Design Reference Architecture 5.0 (DRA5). As part of DRA5, Thermal Protection System (TPS) sizing analysis was performed on a mid L/D rigid aeroshell undergoing a dual heat pulse (aerocapture and atmospheric entry) trajectory. The DRA5 TPS subteam determined that using traditional monolithic ablator systems would be mass expensive. They proposed a new dual-layer TPS concept utilizing an ablator atop a low thermal conductivity insulative substrate to address the issue. Using existing thermal response models for an ablator and insulative tile, preliminary hand analysis of the dual layer concept at a few key heating points indicated that the concept showed potential to reduce TPS masses and warranted further study. In FY09, the followon Entry, Descent and Landing Systems Analysis (EDL-SA) project continued by focusing on Exploration-class cargo or crewed missions requiring 10 to 50 metric tons of landed payload. The TPS subteam advanced the preliminary dual-layer TPS analysis by developing a new process and updated TPS sizing code to rapidly evaluate mass-optimized, full body sizing for a dual layer TPS that is capable of dual heat pulse performance. This paper describes the process and presents the results of the EDL-SA FY09 dual-layer TPS analyses on the rigid mid L/D aeroshell. Additionally, several trade studies were conducted with the sizing code to evaluate the impact of various design factors, assumptions and margins.

McGuire, Mary Kathleen↗

DOE OSTI2023

Dynamic structural and microstructural responses of a metal–organic framework type material to carbon dioxide under dual gas flow and supercritical conditions

The structural and microstructural responses of a model metal–organic framework material, Ni(3-methyl-4,4'-bipyridine)[Ni(CN) 4 ] (Ni-BpyMe or PICNIC-21), to CO 2 adsorption and desorption are reported for in situ small-angle X-ray scattering and X-ray diffraction measurements under different gas pressure conditions for two technologically important cases. These conditions are single or dual gas flow (CO 2 with N 2 , CH 4 or H 2 at sub-critical CO 2 partial pressures and ambient temperatures) and supercritical CO 2 (with static pressures and temperatures adjusted to explore the gas, liquid and supercritical fluid regimes on the CO 2 phase diagram). The experimental results are compared with density functional theory calculations that seek to predict where CO 2 and other gas molecules are accommodated within the sorbent structure as a function of gas pressure conditions, and hence the degree of swelling and contraction in the associated structure spacings and void spaces. Furthermore, these predictions illustrate the insights that can be gained concerning how such sorbents can be designed or modified to optimize the desired gas sorption properties relevant to enhanced gas recovery or to addressing carbon dioxide reduction through carbon mitigation, or even direct air capture of CO 2 .

36 MATERIALS SCIENCE↗

DOE OSTI2026

Multitask graph neural networks for elastoplastic response prediction in dual-phase polycrystals

Microstructure-sensitive prediction of elastoplastic response remains a recurring bottleneck in multiscale damage and fatigue modeling, where large ensembles of statistically distinct polycrystals are required to quantify variability and extreme-value behavior. In this work, we develop a multitask graph neural network (GNN) surrogate that maps dual-phase ferrite–martensite polycrystal microstructures to Statistical Volume Element (SVE)-level elastoplastic Quantities of Interest (QoIs). Each SVE is represented as a grain-adjacency graph, with node features encoding phase, geometry, and crystallographic orientation, and edge features encoding relative misorientation. A message-passing graph convolution generates node embeddings, which are pooled into a graph representation and passed to a multitask regression head that jointly predicts 10 scalar QoIs and vector-valued stress–strain responses in orthogonal loading directions across multiple martensite volume fractions and SVE sizes. Results show high accuracy for scalar QoIs and strong agreement for full stress–strain trajectories, with population envelopes reproducing both median behavior and finite-SVE variability across compositions and partition scales. A unified model trained on pooled volume-fraction data preserves most within-regime accuracy relative to regime-specific models while also capturing the broader cross-regime variation reflected in the pooled test set. Distributional comparisons further demonstrate that the surrogate preserves heterogeneity under SVE partitioning, enabling statistically consistent block-wise random-field construction for mesoscale analyses. Overall, the proposed grain-graph surrogate provides a practical pathway to accelerate ensemble-based studies of SVE-level constitutive variability in dual-phase polycrystals.

Crystal plasticity↗

NASA NTRS1977

A numerical analysis for a comparative study of the pointing accuracy of flexible satellites

The analytical models for flexible satellites have been reported earlier. Numerical results comparing the pointing accuracy of three-axes stabilized, spinning, and dual-spin satellites are presented here. The responses are compared for deterministic and random models with and without external torques. The performances of a uniform control system have been compared to a time-optimal control system for the same base-line configurations.

Huang, T. C.↗

NASA NTRS1992

The direct effects of gravity on the control and output matrices of controlled structure models

The effects of gravity on the dynamic performance of structural control actuators and sensors are dual forms of an additive perturbation that can attenuate or amplify the device response (input or output). The modal modeling of these perturbations is derived for the general case of arbitrarily oriented devices and arbitrarily oriented planes of deformation. A nondimensional sensitivity analysis to identify the circumstances under which the effects of gravity are important is presented. Results show that gravity effects become important when the product of the ratio of the normalized modal slope and the modal displacement is comparable to the ratio of the gravitational acceleration and the product of the beam length and the squared eigenfrequency for a given mode.

Rey, Daniel A.↗

NASA NTRS1984

Aeroelastic effects in multi-rotor vehicles with application to a hybrid heavy lift system. Part 1: Formulation of equations of motion

This report presents a set of governing coupled differential equations for a model of a hybrid aircraft. The model consists of multiple rotor systems connected by an elastic interconnecting structure, with options to add any combination of or all of the following components; i.e., thrusters, a buoyant hull, and an underslung weight. The dynamic equations are written for the individual blade with hub motions, for the rigid body motions of the whole model, and also for the flexible modes of the interconnecting structure. One of the purposes of this study is to serve as the basis of a numerical study aimed at determining the aeroelastic stability and structural response characteristics of a Hybrid Heavy Lift Airship (HHLA). It is also expected that the formulation may be applicable to analyzing stability and responses of dual rotor helicopters such as a Heavy Lift Helicopter (HLH). Futhermore, the model is capable of representing coupled rotor/body aeromechanical problems of single rotor helicopters.

Venkatesan, C.↗

NASA NTRS2016

Heatshield for Extreme Entry Environment Technology (HEEET) Development Status

The Heat shield for Extreme Entry Environment Technology (HEEET) Project is a NASA STMD and SMD co-funded effort. The goal is to develop and mission infuse a new ablative Thermal Protection System that can withstand extreme entry. It is targeted to support NASAs high priority missions, as defined in the latest decadal survey, to destinations such as Venus and Saturn in-situ robotic science missions. Entry into these planetary atmospheres results in extreme heating. The entry peak heat-flux and associated pressure are estimated to be between one and two orders of magnitude higher than those experienced by Mars Science Laboratory or Lunar return missions. In the recent New Frontiers community announcement NASA has indicated that it is considering providing an increase to the PI managed mission cost (PIMMC) for investigations utilizing the Heat Shield for Extreme Entry Environment Technology (HEEET) and in addition, NASA is considering limiting the risk assessment to only their accommodation on the spacecraft and the mission environment. The HEEET ablative TPS utilizes 3D weaving technology to manufacture a dual layer material architecture. The 3-D weaving allows for flat panels to be woven. The dual layer consists of a top layer designed to withstand the extreme external environment while the inner or insulating layer by design, is designed to achieve low thermal conductivity, and it keeps the heat from conducting towards the structure underneath. Both arc jet testing combined with material properties have been used to develop thermal response models that allows for comparison of performance with heritage carbon phenolic. A 50 mass efficiency is achieved by the dual layer construct compared to carbon phenolic for a broad range of missions both to Saturn and Venus. The 3-D woven flat preforms are molded to achieve the shape as they are compliant and then resin infusion with curing forms a rigid panels. These panels are then bonded on to the aeroshell structure. Gaps exist between the panels and these gaps have to be filled with seams. The seam material then has to be bonded on to adjacent panels and also to the structure. The heat-shield assembly is shown in Figure 1. One of the significant challenges we have overcome recently is the design, development and testing of the seam. HEEET material development and the seam concept development have utilized some of the unique test capabilities available in the US. The various test facilities utilized in thermal testing along with the entry environment for Saturn and Venus missions are shown in Figure 2. The HEEET project is currently in its 3rd year of a four-year development. Figure 3 illustrates the key accomplishments to date and the challenges yet to be overcome before the technology is ready for mission infusion. This proposed presentation will cover both progress that has been made in the HEEET project and also the challenges to be overcome that is highlighted in Figure 3. Objective of the HEEET project is to mature the system in time to support the next New Frontiers opportunity and we believe we are well along the way to mission infuse HEEET.

Thermal Protection System↗

NASA NTRS2016

Heat-shield for Extreme Entry Environment Technology (HEEET) Development Status

The Heat shield for Extreme Entry Environment Technology (HEEET) Project is a NASA STMD and SMD co-funded effort. The goal is to develop and mission infuse a new ablative Thermal Protection System that can withstand extreme entry. It is targeted to support NASA's high priority missions, as defined in the latest decadal survey, to destinations such as Venus and Saturn in-situ robotic science missions. Entry into these planetary atmospheres results in extreme heating. The entry peak heat-flux and associated pressure are estimated to be between one and two orders of magnitude higher than those experienced by Mars Science Laboratory or Lunar return missions. In the recent New Frontiers community announcement NASA has indicated that it is considering providing an increase to the PI managed mission cost (PIMMC) for investigations utilizing the Heat Shield for Extreme Entry Environment Technology (HEEET) and in addition, NASA is considering limiting the risk assessment to only their accommodation on the spacecraft and the mission environment. The HEEET ablative TPS utilizes 3D weaving technology to manufacture a dual layer material architecture. The 3-D weaving allows for flat panels to be woven. The dual layer consists of a top layer designed to withstand the extreme external environment while the inner or insulating layer by design, is designed to achieve low thermal conductivity, and it keeps the heat from conducting towards the structure underneath. Both arc jet testing combined with material properties have been used to develop thermal response models that allows for comparison of performance with heritage carbon phenolic. A 50% mass efficiency is achieved by the dual layer construct compared to carbon phenolic for a broad range of missions both to Saturn and Venus. The 3-D woven flat preforms are molded to achieve the shape as they are compliant and then resin infusion with curing forms a rigid panels. These panels are then bonded on to the aeroshell structure. Gaps exist between the panels and these gaps have to be filled with seams. The seam material then has to be bonded on to adjacent panels and also to the structure. The heat-shield assembly is shown in Figure 1. One of the significant challenges we have overcome recently is the design, development and testing of the seam. HEEET material development and the seam concept development have utilized some of the unique test capabilities available in the US. The various test facilities utilized in thermal testing along with the entry environment for Saturn and Venus missions are shown in Figure 2. The HEEET project is currently in it's 3rd year of a four-year development. Figure 3 illustrates the key accomplishments to-date and the challenges yet to be overcome before the technology is ready for mission infusion. This proposed presentation will cover both progress that has been made in the HEEET project and also the challenges to be overcome that is highlighted in Figure 3. Objective of the HEEET project is to mature the system in time to support the next New Frontiers opportunity and we believe we are well along the way to mission infuse HEEET.

TPS↗

NASA NTRSDate not supplied

Prediction of High-Latitude Ionospheric Electrodynamics Using the Machine Learning Based Auroral Ionospheric Electrodynamics Model

We introduce a new framework for Machine-Learning (ML) based Auroral Ionosphere Model (ML-AIM). ML-AIM solves a current continuity equation by utilizing the ML model of Field Aligned Currents (FACs) of Kunduri et al., 2020 (https://doi.org/10.1029/2020JA027908), the FAC-derived aurora conductance model of Robinson et al., 2020 (https://doi.org/10.1029/2020JA028008), and the solar irradiance conductance model of Moen & Brekke (1993). The ML-AIM inputs are 60min time histories of solar wind plasma, interplanetary magnetic fields (IMF), and geomagnetic indices, and its outputs are ionospheric electric potential, electric fields, Pederson/Hall currents, and Joule Heating. We conduct two ML-AIM simulations for a weak geomagnetic activity on 14 May 2013 and a geomagnetic storm on 7-8 September 2017. ML-AIM produces reasonable ionospheric potential patterns such as two cell convection patterns and the enhancement of electric potentials during active times. The cross polar cap potential drop from ML-AIM is also comparable to the ones from the Weimer 2005 model, Super Dual Auroral Radar Network (SuperDARN), and Defense Meteorological Satellite Program (DMSP) F17 observations. ML-AIM is unique in a sense that it predicts ionospheric responses to the time-varying solar wind and geomagnetic conditions, while other traditional empirical model like Weimer 2005 is designed to provide static ionospheric conditions under steady solar wind/IMF conditions. In future, ML-AIM will include ML-based models of aurora precipitation and ionospheric conductance, improving its performance during active times.

H. K. Connor↗

NASA NTRS1976

An experimental determination in Calspan Ludwieg tube of the base environment of the integrated space shuttle vehicle at simulated Mach 4.5 flight conditions (test IH5 of model 19-OTS)

A model test program was conducted to determine heat transfer and pressure distributions in the base region of the space shuttle vehicle during simulated launch trajectory conditions of Mach 4.5 and pressure altitudes between 90,000 and 210,000 feet. Model configurations with and without the solid propellant booster rockets were examined to duplicate pre- and post-staging vehicle geometries. Using short duration flow techniques, a tube wind tunnel provided supersonic flow over the model. Simultaneously, combustion generated exhaust products reproduced the gasdynamic and thermochemical structure of the main vehicle engine plumes. Heat transfer and pressure measurements were made at numerous locations on the base surfaces of the 19-OTS space shuttle model with high response instrumentation. In addition, measurements of base recovery temperature were made indirectly by using dual fine wire and resistance thermometers and by extrapolating heat transfer measurements.

Drzewiecki, R. F.↗

DOE OSTI2024

Power capture and power take-off load of a self-balanced dual-flap oscillating surge wave energy converter

Wave energy converters are an important part of future renewable energy infrastructure. Predicting their power matrix, capture width ratio, and power take-off loads at a targeted site is required for performance assessment before deployment. Because their testing is very expensive, numerical modeling and simulations play a significant role in those assessments. Linear potential flow theory has limited accuracy under large amplitude wave forcing. More accurate predictions can be obtained by using higher-fidelity models, which are computationally expensive. We present a framework for multi-fidelity numerical simulations to determine the hydrodynamic response, wave capture capability, and power take-off load of a full-scale dual-flap oscillating surge wave energy converter. This design exploits out-of-phase motion by setting the distance between the flaps to half the wavelength of the most occurring wave. The simulations are validated using a 1:10 model experiments in a wave tank. Based on these validations, it was determined that Euler simulations provide an acceptable prediction with 90% reduction in computational time with only 11% error. Utilizing Euler simulations at full-scale, the results demonstrate that the annual electrical energy output is 1.79 GWh under regular wave conditions. Here, one significant improvement over single-flap designs is the capture width ratio which exceeds unity.

16 TIDAL AND WAVE POWER↗

NASA NTRS2023

The Statistical Emulators of GGCMI Phase 2: Responses of Year-to-Year Variation of Crop Yield to CO 2 , Temperature, Water and Nitrogen Perturbations

Understanding the impact of climate change on year-to-year variation of crop yield is critical to global food stability and security. While crop model emulators are believed to be lightweight tools to replace the models, few emulators have been developed to capture such interannual variation of crop yield in response to climate variability. In this study, we developed a statistical emulator with a machine learning algorithm to reproduce the response of year-to-year variation of four crop yields to CO 2 (C), temperature (T), water (W), and nitrogen (N) perturbations defined in the Global Gridded Crop Model Intercomparison Project (GGCMI) phase 2. The emulators were able to explain more than 52 % of the variance of simulated yield and performed well in capturing the year-to-year variation of global average and gridded crop yield over current croplands in the baseline. With the changes in CO 2 –temperature–water–nitrogen (CTWN) perturbations, the emulators could reproduce the year-to-year variation of crop yield well over most current cropland. The variation of R and the mean absolute error was small under the single CTWN perturbations and dual-factor perturbations. These emulators thus provide statistical response surfaces of yield, including both its mean and interannual variability, to climate factors. They could facilitate spatiotemporal downscaling of crop model simulation, projecting the changes in crop yield variability in the future and serving as a lightweight tool for multi-model ensemble simulation. The emulators enhanced the flexibility of crop yield estimates and expanded the application of large-ensemble simulations of crop yield under climate change.

Climate change↗

NASA NTRS1977

Manual control of yaw motion with combined visual and vestibular cues

Measurements are made of manual control performance in the closed-loop task of nulling perceived self-rotation velocity about an earth-vertical axis. Self-velocity estimation was modelled as a function of the simultaneous presentation of vestibular and peripheral visual field motion cues. Based on measured low-frequency operator behavior in three visual field environments, a parallel channel linear model is proposed which has separate visual and vestibular pathways summing in a complementary manner. A correction to the frequency responses is provided by a separate measurement of manual control performance in an analogous visual pursuit nulling task. The resulting dual-input describing function for motion perception dependence on combined cue presentation supports the complementary model, in which vestibular cues dominate sensation at frequencies above 0.05 Hz. The describing function model is extended by the proposal of a non-linear cue conflict model, in which cue weighting depends on the level of agreement between visual and vestibular cues.

Zacharias, G. L.↗

DOE OSTI2025

A staged deep learning approach to spatial refinement in 3D temporal atmospheric transport

High-resolution spatiotemporal simulations effectively capture the complexities of atmospheric plume dispersion in complex terrain. However, their high computational cost makes them impractical for applications requiring rapid responses or iterative processes, such as optimization, uncertainty quantification, or inverse modeling. To address this challenge, this work introduces the Dual-Stage Temporal Three-dimensional UNet Super-resolution (DST3D-UNet-SR) model, a highly efficient deep learning model for plume dispersion predictions. DST3D-UNet-SR is composed of two sequential modules: the temporal module (TM), which predicts the transient evolution of a plume in complex terrain from low-resolution temporal data, and the spatial refinement module (SRM), which subsequently enhances the spatial resolution of the TM predictions. We train DST3D-UNet-SR using a comprehensive dataset derived from high-resolution large eddy simulations (LES) of plume transport. We propose the DST3D-UNet-SR model to significantly accelerate LES of three-dimensional (3D) plume dispersion by three orders of magnitude. Additionally, the model demonstrates the ability to dynamically adapt to evolving conditions through the incorporation of new observational data, substantially improving prediction accuracy in high-concentration regions near the source.

3D temporal sequences↗

NASA NTRS1974

Statistical analysis of low level atmospheric turbulence

The statistical properties of low-level wind-turbulence data were obtained with the model 1080 total vector anemometer and the model 1296 dual split-film anemometer, both manufactured by Thermo Systems Incorporated. The data obtained from the above fast-response probes were compared with the results obtained from a pair of Gill propeller anemometers. The digitized time series representing the three velocity components and the temperature were each divided into a number of blocks, the length of which depended on the lowest frequency of interest and also on the storage capacity of the available computer. A moving-average and differencing high-pass filter was used to remove the trend and the low frequency components in the time series. The calculated results for each of the anemometers used are represented in graphical or tabulated form.

Tieleman, H. W.↗