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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A digital twin platform for building performance monitoring and optimization: Performance simulation and case studies

Advancements in sensor technology, data analytics, affordable compute, and communication infrastructure have paved the way for Digital Twin technology in optimizing building operations and controls. This study presents the development of an open and interoperable web-based Digital Twin platform for integrating diverse data streams and facilitating effective user interactions. The platform utilizes modern technologies for the web framework and time-series data management, ensuring scalability and responsiveness. The backend supports seamless integration of diverse data sources and emulators, incorporating data from building sensors and meters, external weather Application Programming Interfaces, and advanced EnergyPlus simulation models of the building and its energy systems including the Distributed Energy Resources that are formulated in Functional Mockup Units. A simulation case study was conducted with FlexLab, a test facility on Lawrence Berkeley National Laboratory campus. The case study includes normal operations, Distributed Energy Resource integration, and power outage scenarios, to illustrate the Digital Twin’s ability to provide critical insights into energy performance and thermal resilience. The results demonstrated the platform’s potential as a decision-support tool for optimizing building energy performance and enhancing resilience against extreme weather events. Future work will focus on deploying the Digital Twin platform to a real building for field validation, extending its capabilities to cover more scenarios such as bidirectional Electric Vehicle interactions, and enhancing user engagement.

EnergyPlus↗
DOE OSTI2025

Optimization of simulated high-field side lower hybrid current drive coupling using machine learning predictions of scrape-off layer density

Lower hybrid current drive (LHCD) is a potential source of non-inductive off-axis current drive (CD) for tokamaks. Although LHCD has been successfully deployed on a number of tokamaks, it is highly sensitive to the scrape-off layer (SOL) conditions local to the LHCD launcher. Large gaps between the launcher and plasma core, SOL turbulence, or edge density perturbations due to edge-localized modes can hamper CD or cause large reflected power. These coupling issues in part motivated the installation of an LHCD launcher on the high-field side (HFS) of DIII-D. On the HFS, the SOL is less turbulent and more controllable compared to the low-field side. This quiescence may result in more predictable edge conditions and thus a more predictable CD. Here, in this work, HFS SOL reflectometry measurements are predicted from global plasma parameters using machine learning models. The SOL predictions coupled with the full-wave simulation of the LHCD launcher allow for the prediction of reflected power, directivity, and arcing risk before the discharge. Launcher performance is then optimized using multi-objective Bayesian optimization, finding the shot parameters that result in an optimal SOL density that maximizes CD while minimizing the risk of arcing. The predictions and optimizations of LHCD performance are then accelerated using a surrogate model of the full-wave LHCD simulation.

Bayesian optimization↗
DOE OSTI2020

Multiphase Reacting Flow Simulations and Optimization of Commercial-Scale Aerobic Bioreactors

Aerobic bioreactors are widely used in the synthesis of value-added products in pharmaceutical and biotechnology industries, wherein microbial bioreactions aid in the conversion of sugars to macromolecules. These reactors are also being actively investigated as a cost-effective pathway for the production of low-value commodities such as biofuels and animal feed. Reactor scale-up is one of the important challenges when designing these systems. Gas and liquid phase transport, mass-transfer, and mixing physics at large length scales can significantly affect microbial conversion rates, particularly when the microbial reaction requires a narrow set of conditions. These phenomena are difficult to study in small-scale bench-top reactors that are typically well-mixed. Predictive computational fluid dynamics (CFD) based simulations can therefore aid in the design and optimization of these reactors. This work presents multiphase Euler-Euler CFD simulations of commercial-scale (~ 500 m3) aerobic bioreactors. Our mathematical model treats the gas and liquid as interpenetrating phases. This approach reduces the computational complexity of tracking individual gas bubbles that are several orders of magnitude smaller than reactor dimensions. We solve the Reynolds averaged Navier-Stokes (RANS) multiphase equations that account for phase and chemical species transport, interphase mass and momentum transfer and uses a phenomenological model for oxygen uptake by microbes. We use a customized solver derived from open-source CFD toolbox, OpenFOAM, to perform these simulations, which has been validated against small-scale reactors in our previous work. This work examines the performance of three different reactor designs, viz. bubble column reactor, airlift reactor with an internal draft tube, and a stirred-tank reactor with Rushton impellers. Reactor oxygen mass-transfer coefficient, gas hold-up, and oxygen distribution are critically analyzed among reactors, and sensitivity studies pertaining to gas flow rates and reactor geometry will be presented.

09 BIOMASS FUELS↗
NASA NTRS2004

Genetic Optimization and Simulation of a Piezoelectric Pipe-Crawling Inspection Robot

Using the DarwinZk development software, a genetic algorithm (GA) was used to design and optimize a pipe-crawling robot for parameters such as mass, power consumption, and joint extension to further the research of the Miniature Inspection Systems Technology (MIST) team. In an attempt to improve on existing designs, a new robot was developed, the piezo robot. The final proposed design uses piezoelectric expansion actuators to move the robot with a 'chimneying' method employed by mountain climbers and greatly improves on previous designs in load bearing ability, pipe traversing specifications, and field usability. This research shows the advantages of GA assisted design in the field of robotics.

Hollinger, Geoffrey A.↗
DOE OSTI2022

The impact of hurricane disturbances on a tropical forest: implementing a palm plant functional type and hurricane disturbance module in ED2-HuDi V1.0

Hurricanes commonly disturb and damage tropical forests. Hurricane frequency and intensity are predicted to change under the changing climate. The short-term impacts of hurricane disturbances to tropical forests have been widely studied, but the long-term impacts are rarely investigated. Modeling is critical to investigate the potential response of forests to future disturbances, particularly if the nature of the disturbances is changing with climate. Unfortunately, existing models of forest dynamics are not presently able to account for hurricane disturbances. Therefore, we implement the Hurricane Disturbance in the Ecosystem Demography model (ED2) (ED2-HuDi). The hurricane disturbance includes hurricane-induced immediate mortality and subsequent recovery modules. The parameterizations are based on observations at the Bisley Experimental Watersheds (BEW) in the Luquillo Experimental Forest in Puerto Rico. We add one new plant functional type (PFT) to the model – Palm, as palms cannot be categorized into one of the current existing PFTs and are known to be an abundant component of tropical forests worldwide. The model is calibrated with observations at BEW using the generalized likelihood uncertainty estimation (GLUE) approach. The optimal simulation obtained from GLUE has a mean relative error of –21 %, –12 %, and –15 % for stem density, basal area, and aboveground biomass, respectively. The optimal simulation also agrees well with the observation in terms of PFT composition (+1 %, –8 %, –2 %, and +9 % differences in the percentages of “Early”, “Mid”, “Late”, and “Palm” PFTs, respectively) and size structure of the forest (+0.8 % differences in the percentage of large stems). Lastly, using the optimal parameter set, we study the impact of forest initial condition on the recovery of the forest from a single hurricane disturbance. The results indicate that, compared to a no-hurricane scenario, a single hurricane disturbance has little impact on forest structure (+1 % change in the percentage of large stems) and composition (<1 % change in the percentage of each of the four PFTs) but leads to 5 % higher aboveground biomass after 80 years of succession. The assumption of a less severe hurricane disturbance leads to a 4 % increase in aboveground biomass.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Adjoint-Based Mesh Adaptation and Shape Optimization for Simulations with Propulsion

Objectives: Reliable evaluation of mass flow rates through permeable boundaries - Estimate and control discretization error- Consider both computational domain outflow and inflow- Applicable to simulating propulsion-system effects, as well as secondary flow paths - Explore feasibility of handling more general outputs at domain boundaries. Design optimization subject to mass-flow-rate constraints - Improve aerodynamic performance and reduce noise due to sonic boom - Control discretization error in design space to improve confidence in final designs.

Nemec, Marian↗
DOE OSTI2021

Parametrized Hamiltonian simulation using quantum optimal control

Analog quantum simulation offers a hardware-specific approach to studying quantum dynamics, but mapping a model Hamiltonian onto the available device parameters requires matching the hardware dynamics. In this work, we introduce a paradigm for quantum Hamiltonian simulation that leverages digital decomposition techniques and optimal control to perform analog simulation. We validate this approach by constructing the optimal analog controls for a superconducting transmon device to emulate the dynamics of an extended Bose-Hubbard model. We demonstrate the role of control time, digital error, and pulse complexity, and we explore the accuracy and robustness of these controls. We conclude by discussing the opportunity for implementing this paradigm in near-term quantum devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Simultaneous optimization of simulated moving bed adsorption and distillation for 2,3‐butanediol recovery

Abstract A combined simulated moving bed (SMB) and distillation separation scheme is developed to recover 2,3‐butanediol (BDO) from a dilute fermentation broth. The scheme was integrated into a lignocellulosic biorefinery that produces hydrocarbon fuels from corn stover with BDO as an intermediate. BDO recovery is one of the most challenging processes in this biorefinery; and given the high associated energy duties, direct distillation is considered cost‐prohibitive. An alternative separation is SMB adsorption in nanoporous materials, which can reject 90% of the water and reduce subsequent distillation costs. Rigorous models were used to optimize the SMB and distillation simultaneously. The separation can be added to the biorefinery while keeping the projected minimum fuel selling price (MFSP) below $0.66 USD (US dollars) per liter gasoline‐equivalent ($2.50/GGE, gallon gasoline equivalent). Finally, sensitivity analyses were conducted to assess the effects of cost and lifetime of the adsorbent, titer concentration, and BDO purity.

09 BIOMASS FUELS↗
DOE OSTI2025

Fleet Algorithm Design for Pooled Rideshare: Integrating Human Factors, Simulation, and Optimization

This dissertation explores the study the integration of human factors modeling and rideshare fleet control algorithms. Pooled rideshare is a unique transportation mode offering that allows riders increased flexibility and accessibility over public transportation, and decreased cost relative to personal vehicles or traditional rideshare. Additionally, relative to personal vehicles, pooled rideshare offers reduced costs and options for those with difficulty obtaining transportation. Prior research in the space typically focused on modeling human behavior, or optimizing system performance, but a lack of integration of the concepts leads to unrealistic or underutilized outcomes. To tackle this problem, novel rideshare assignment, and repositioning strategies were designed and implemented in a simulation environment. Through a series of successive studies, improvements to current rideshare processes were identified, and beneficial outcomes for profitability, accessibility, and traffic were explored. Further, improved metrics to assess rideshare performance were designed and analyzed in the context of improved rideshare offerings. This research contributes to the field of transportation by tackling novel but pragmatic approaches to challenges facing the rideshare industry. Through the course of this dissertation, rideshares impacts on users, operators, and even regulators will be explored in detail. The justification behind the use of a simulation environment, a set of simulated regional models for testing, and the focus on realism and deployability is illustrated. The research identifies holes in potential markets for the use of both private, and public rideshare systems.

Paul, Joseph↗
DOE OSTI2021

Probabilistic Resilience of DER Systems - A Simulation Assisted Optimization Approach

Energy systems resilience is becoming increasingly important as the frequency of major grid outages increases. In this work, we present a methodology to optimize a behind-tlie-meter distributed energy resource system to sustain a site's critical loads during a pre-defined outage period. With the fixed system design, we then propose an outage simulation approach to estimate the resilience potential of the DER system to sustain loads beyond the fixed outage period - a yearlong resilience performance analysis. We apply statistical analysis to assess the system's resilience performance over a broader parametric problem space on an hourly, monthly, and yearly basis. We demonstrate the impact of the pre-defined outage period on the resilience performance through a case study. Results show that the probability of surviving a random outage of a given duration changes from 20% to 95% when the outage is modeled for a weekday instead of a weekend for the given load-profile.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2021

Probabilistic Resilience of DER Systems - A Simulation Assisted Optimization Approach

Energy systems resilience is becoming increasingly important as the frequency of major grid outages increases. In this work, we present a methodology to optimize a behind-the-meter distributed energy resource system to sustain a site's critical loads during a pre-defined outage period. With the fixed system design, we then propose an outage simulation approach to estimate the resilience potential of the DER system to sustain loads beyond the fixed outage period - a yearlong resilience performance analysis. We apply statistical analysis to assess the system's resilience performance over a broader parametric problem space on an hourly, monthly, and yearly basis. We demonstrate the impact of the pre-defined outage period on the resilience performance through a case study. Results show that the probability of surviving a random outage of a given duration changes from 20% to 95% when the outage is modeled for a weekday instead of a weekend for the given load-profile.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Full-torus impurity transport simulation for optimizing plasma discharge operation using a multi-species impurity powder dropper in the large helical device

The transport of impurities supplied by a multi-species impurity powder dropper (IPD) in the large helical device (LHD) is investigated using a three-dimensional peripheral plasma fluid code (EMC3-EIRENE) coupled with a dust transport simulation code (DUSTT). The trajectories of impurity powder particles (Boron, Carbon, Iron, and Tungsten) dropped from the IPD and the impurity transport in the peripheral plasma are studied in a full-torus geometry. The simulation reveals an appropriate size of the impurity powder particles and an optimum operational range of the dust drop rates for investigating the impurity transport without inducing radiation collapse. The simulation also predicts a favourable plasma discharge condition for wall conditioning (boronization) using the IPD in order to deposit boron to high plasma flux and neutral particle density areas in the divertor region in the inboard side of the torus.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1990

Computer Simulation For Multilevel Optimization Of Design

New simulator for multilevel optimization of complex hierarchical systems reduces cost of analysis in experimentation with multilevel design-optimization algorithms. Computer program mimics qualitative behavior and data couplings that occur among subsystems of complex engineering system, such as car, aircraft, or building. Eliminates engineering analyses in subsystems by replacing them with judiciously-chosen analytical functions. Serves as tool for development of strategy for multilevel optimization of design.

Padula, Sharon L.↗
NASA NTRSDate not supplied

Performance Analysis of Magnetohydrodynamic Drag Modulation for Actively Controlled Aerocapture at Neptune

While the Ice Giants are a top priority for flagship missions in the NASA’s near-term future, current technologies limit the scientific payload and mission timeline for future Uranian and Neptunian missions due to the need for fuel for orbit insertion maneuvers. Thus, to maximize the scientific potential of future missions, atmospheric aerocapture has been heavily researched. While atmospheric aerocapture simulations have proven enabling for capturing around Neptune, its deep atmospheric pass requires an aeroshell with robust thermal protection systems (TPS). Magnetohydrodynamically-controlled aerocapture serves as a potential solution to the limitations of both fully propulsive orbit insertion and aerodynamically controlled aerocapture. Through NASA Langley’s high-fidelity flight dynamics simulation, the Program to Optimize Simulated Trajectories II, both the aerodynamic-only and magnetohydrodynamic aerocapture methods were simulated and compared for identical missions to Neptune. After applying an optimized numerical predictor-corrector guidance algorithm for both methods, the results showed that magnetohydrodynamics has not only the control authority to successfully capture around Neptune, but also the unique advantage of a shallower atmospheric pass, decreasing the maximum heat load and the required TPS mass.

Danny N. Nguyen↗
NASA NTRS1978

Human operator identification model and related computer programs

Four computer programs which provide computational assistance in the analysis of man/machine systems are reported. The programs are: (1) Modified Transfer Function Program (TF); (2) Time Varying Response Program (TVSR); (3) Optimal Simulation Program (TVOPT); and (4) Linear Identification Program (SCIDNT). The TV program converts the time domain state variable system representative to frequency domain transfer function system representation. The TVSR program computes time histories of the input/output responses of the human operator model. The TVOPT program is an optimal simulation program and is similar to TVSR in that it produces time histories of system states associated with an operator in the loop system. The differences between the two programs are presented. The SCIDNT program is an open loop identification code which operates on the simulated data from TVOPT (or TVSR) or real operator data from motion simulators.

Kessler, K. M.↗
DOE OSTI2022

Simulation and Optimization of Volatile Fatty Acid Upgrading Strategies for Sustainable Transportation Fuel Production

Underutilized wet waste is a promising feedstock for production of carbon-neutral or carbon-negative liquid transportation fuels. Arrested methanogenesis of wet wastes by microbes, which produces mixtures of C2-C8 carboxylic acids (volatile fatty acids, VFAs), is practiced industrially at a pilot scale and the VFA products can be catalytically upgraded to molecules suitable for use as transportation fuels (alcohols and alkanes) via sequential ketonization and hydrogenation, both steps of which have been demonstrated with high (>90%) yield at the lab scale. We present in this work a simulation-based decision-making framework which evaluates upgrading strategies of VFAs to alcohol- and hydrocarbon-based neat and blended diesel, jet, and gasoline fuels. The processes utilize sequential upgrading steps (ketonization and hydrogenation) accompanied by one distillation step (either separating VFAs before ketonization or alcohols after ketone hydrogenation) to form two liquid streams: a light alcohol stream best suited as a light-duty fuel and a heavy alcohol or hydrocarbon stream best suited as a diesel or jet fuel. Suitability of the liquid products as transportation fuels and maximum blending levels with petrofuels comes from simulation of critical fuel properties (boiling point, flash point, lower heating value, viscosity, melting point, water solubility, and cetane/octane number). Catalytic upgrading steps and fuel property mixing models used by the simulation are experimentally validated. We demonstrate the flexibility of the decision-making algorithm by evaluating processing scenarios for experimentally-observed VFA profiles with varied carbon chain length distributions. Processing scenarios are optimized for either maximum total renewable carbon utilization or production of heavy-duty (jet or diesel) fuels. We evaluate the economic viability and CO2 emissions of each proposed upgrading scenario using techno-economic and life cycle analyses. The decision-making framework developed in this work can also be used to down-select promising strategies for upgrading of other bio-based feedstocks to sustainable fuels and chemicals.

aviation fuel↗
DOE OSTI2025

Magnetized liner inertial fusion platform development to assess performance scaling with drive parameters

Magnetized liner inertial fusion (MagLIF) experiments have demonstrated fusion-relevant ion temperatures up to 3.1 keV and thermonuclear production of up to 1.1 × 1013 deuterium–deuterium neutrons. This performance was enabled through platform development that provided increases in applied magnetic field, coupled preheat energy, and drive current. Advanced coil designs with internal reinforcement enabled an increase from 10 to 20 T. An improved laser pulse shape, beam smoothing, and thinner laser entrance foils increased preheat energy coupling from less than 1 to 2.3 kJ. A redesign of the final transmission line and load region increased peak load current from 16 to 20 MA. The wider range of input parameters was leveraged to study target performance trends with preheat energy, applied magnetic field, and peak load current. Ion temperature and neutron yield generally followed trends in two-dimensional clean Lasnex calculations. Stagnation performance improved with peak load current when other input parameters were also increased such that convergence was maintained. This dataset suggests that reducing convergence to less than 30 would improve predictability of target performance. Lasnex was used to identify a simulation-optimized scaling path, which suggests 10+ kJ of fusion yield is possible on the Z facility with achievable input parameters. This path also indicates >10 MJ could be generated through volume burn on a future facility with a path to high yield (>200 MJ) using cryogenic dense fuel layers. The newly developed MagLIF platform enables exploration of both this simulation optimized scaling path and a recently developed similarity-scaling path.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A Simulation and Optimization Framework for Managing Wind-Driven Loading on PV Systems

As PV modules continue to trend toward larger, thinner, and more flexible forms they grow more susceptible to damage from dynamic wind loading. As a result, understanding the impact of wind on PV systems, particularly when mounted on solar-tracking hardware, and identifying robust, stable array layouts and stow strategies is becoming increasingly important for the PV community. We are developing an open-source software package, PVade (PV aerodynamic design engineering), to simulate the cascading fluid-structure interaction that occurs within solar-tracking arrays to enable researchers to test hardware, layout, and tracker control changes, leading to enhanced stability and a reduction in wind-driven damage. We will give an overview of the PVade software and present the latest outcomes from our ongoing validation campaign in which we compare statistical structural responses with field data. From there, we will present simulated results from a larger, multi-row array and highlight the effect of varying tracker angles on stability as measured by both acceleration and deformation, focusing on the stability differences between positive and negative tilt angles.

fluid structure interaction↗