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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Public – Private Partnership to Promote Efficient Manufacturing and Workforce Development (IAC Final Technical Report)

Through delivering ninety (90) energy assessments to small- and medium-sized manufacturing facilities in and around Tennessee, significant understandings were gained through providing detailed energy assessment reports to manufacturers and training seventy-seven (77) engineering students in which thirty-five (35) certified IAC students were recognized by DOE. The robust involvement of Tennessee Valley Authority (TVA), local utility and Tennessee Tech’s Cybersecurity Education, Research, and Outreach Center (CEROC) in majority of assessments made the technical operation very effective where leaded to 40.5% implementation rate of energy recommendations. Other benefits of the award to the public are a dynamic modeling tool capable of analyzing existing cooling towers for energy use optimization was developed and presented to DOE IAC, providing technical assistance to non-participating manufacturers in the form of workshop and training, publishing fifteen (15) peer-reviewed conference and journal papers as well as a book chapter in the area of industrial energy efficiency field, assisting the TVA Magnolia Combined Cycle Power Plant to become the First 50001 Ready Certified Power Plant in the U.S. through briefing them on ISO 50001 and 50001 Ready as well as providing an energy assessment to the plant, assisted the new IAC center at Clemson University with on-site and remote support, and provided assessment and training in unique areas of water, waste water, cyber security and smart manufacturing to our clients, students and community.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1999

Development of a Portable, Ground-based Ozone Lidar Instrument for Tropospheric Ozone Research and Educational Training

The objective of this research project is to develop a portable, eye-safe, ground-based ozone lidar instrument specialized for ozone differential absorption lidar (DIAL) measurements in the troposphere. This research project directly supports the goal of NASA's Earth Science Enterprise to understand the distribution and budget of tropospheric ozone (objective 1.5 of the Earth Science Strategic Enterprise Plan, 1998-2002). It can participate in ground validation experiments for TES, a tropospheric ozone satellite mission due to be launched in 2002. It can also be utilized for correlative ground measurements in future GTE (Global Tropospheric Experiment) and space-based ozone lidar missions, such as ORACLE. Multiple ground-based ozone lidar systems would improve the data obtained through current ozone-sonde networks. This prototype instrument could to serve as the basic unit for these and other future monitoring projects requiring multi-instrument networks, such as that proposed for the Global Tropospheric Ozone Project (GTOP). GTOP is currently being formulated by a scientific panel of the International Global Atmospheric Chemistry Project to meet its goal to better understand the processes that control the global distribution of tropospheric ozone. In order for the lidar to be widely deployed in networks, it must be fairly easy to use and maintain as well as being cost-competitive with a ground station launching ozonesondes several times a day. A second 2-year grant to continue this effort with students participating in ground tests and system improvements has been awarded by the Office of Equal Employment Opportunities (OEOP). This project also supports existing NASA lidar missions through its development of advanced, compact lidar technology. Innovations in both transmitters and receivers have been made in this project. Finally, this system could be modified in the future to probe more deeply into the stratosphere. This could be accomplished by increasing the emitted energy or optimizing the wavelengths for this purpose. In addition to NASA, this system has applications to the EPA, NOAA, and the DOD. An AFOSR grant has been awarded based on the results of this effort to fund advanced transmitter development at medium (20-40 mJ) energies. A second proposal to the DOD with a letter of support from Air Force Research Laboratory, has been submitted to extend this uv laser technology to 100 mJ levels. Thus, this project has enabled students and faculty at Hampton University to begin to develop research efforts in support of the mission of the DOD. This instrument will be based at Hampton University (HU) to meet our educational goal to train students in lidar technology as well as atmospheric ozone data analysis and interpretation. It will be also available for off-site measurement campaigns and will serve as a test bed for further instrument development. Later development beyond this grant to extend the scientific usefulness of the instrument may include incorporation of an aerosol channel and upgrading the laser to make stratospheric ozone measurements. Seven undergraduates, three graduate students, and one postdoctoral. researcher (formerly an HU student) have been active participants in this research effort.

Chyba, Thomas↗
DOE OSTI2023

Density functional study of atomic arrangements in CrMnFeCoNi high-entropy alloy and their impact on vacancy formation energy and segregation

Here, using the density functional theory-coupled Monte Carlo approach, we explored the chemical short-range order (SRO) and element segregation in equimolar CrMnFeCoNi alloy. We found that state-of-the-art approximation of random element distribution is only applicable at > 1100 K close to the melting temperature, while the Cr-Cr repulsion driving the system stabilization and accompanying the formation of cubic Cr sublattice, and mild Ni-Ni attraction are the most prominent pair interactions at lower temperatures. Chemical potential and vacancy formation energy calculations indicate that Cr is most sensitive to the local chemical environment, making Cr atoms most stabilized when the preferred SRO is introduced. While the vacancy formation is predicted equally probable among five constituting elements in the random solid solution, Cr and Ni atoms show the lowest vacancy formation energies in the structure with SRO. Furthermore, distinct element segregation was predicted in the vicinity of planar defects, including symmetric tilt grain boundary and stacking fault, which we correlated to the site- and chemistry-dependent atomic volume and bond lengths. It suggests that the local mechanical strain and bond energy induce the SRO development and element segregation: Namely, the system takes advantage of segregation of Ni atoms having large atomic volume or Cr-Cr pairs having elongated bond lengths to fill in the excess volume at defects that relaxes the mechanical strain field and optimizes bond energy distribution. The correlation between the SRO and properties of CrMnFeCoNi alloy needs further investigations, which is expected to greatly help understand and control the properties of high-entropy alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Continuous-time look-ahead flexible ramp scheduling in real-time operation

This paper develops a novel continuous-time look-ahead optimization model for co-optimizing balancing energy and flexible ramp products in real-time power systems operation. In addition, a continuous-time day-ahead operation model is developed to commit and schedule an adequate subset of generating units for providing balancing energy and ramping requirements in real-time operation. The up and down flexible ramp products are defined as continuous-time decision trajectories that continuously supply the real-time up and down ramping requirements of the system. The deliverability of flexible ramp products is secured through reserving the respective power requirements in generation capacity constraints of generating units. A function space solution method is proposed to reduce the dimensionality of day-ahead and real-time models through projecting them into finite-dimensional function spaces spanned by Bernstein polynomials, where the real-time operation decisions are modeled with a higher accuracy level than day-ahead decisions. Simulations are conducted on the IEEE-RTS system using CAISO load data, and the numerical results showcase the effectiveness of the proposed model in supplying the energy and flexible ramp requirements and avoiding ramping scarcity in the system, while reducing the operation costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1976

Clean fuels from biomass

The paper discusses the U.S. resources to provide fuels from agricultural products, the present status of conversion technology of clean fuels from biomass, and a system study directed to determine the energy budget, and environmental and socioeconomic impacts. Conversion processes are discussed relative to pyrolysis and anaerobic fermentation. Pyrolysis breaks the cellulose molecules to smaller molecules under high temperature in the absence of oxygen, wheras anaerobic fermentation is used to convert biomass to methane by means of bacteria. Cost optimization and energy utilization are also discussed.

Hsu, Y.-Y.↗
NASA NTRS1991

Theoretical characterization of the potential energy surface for the reversible reaction H + O2 yields HO2(asterisk) yields OH + O. III - Computed points to define a global potential energy surface

Computed energies and geometries are reported which, combined with previously published calculations, permit a global representation of the potential energy surface for the reaction H + O2 yields HO2(asterisk) yields OH + O. These new calculations characterize the potential energy surface (PES) for all H atom angles of approach to O2 and for the region of the inner repulsive wall. The region of the T-shaped H-O2 exchange saddle point is connected with the constrained energy minimum (CEM) path, and a new collinear H-O2 exchange saddle point is characterized which lies only 9 kcal/mol above the H + O2 asymptote. A vibrational analysis which utilizes local cubic and quartic polynomial representations of the PES along the CEM path has been carried out. Optimal geometries, energies, and harmonic frequencies are reported along with anharmonic analyses for the O2 and OH asymptotes and for the HO2 minimum region of the PES.

Walch, Stephen P.↗
DOE OSTI2024

Optimization-Based Model Reduction Scheme for Renewable Energy Power Plants Using Standardized Testing Scenarios

This paper presents an optimization-based model reduction scheme for renewable energy (RE) power plants consisting of inverter-based resources (IBRs) operating in grid-following (GFL) or grid-forming (GFM) modes. More importantly, the datasets feeding the optimization-based model reduction scheme are generated and re-used through the standardized grid-interactive testing scenarios. Particularly, the proposed scheme makes use of the power plant point of common coupling (PCC) measurements of various quantities specified by standardized tests (e.g., voltage and frequency ride through) as per IEEE 2800, to estimate the parameters of the reduced-order model such that its dynamic performance aligns with the original detailed power plant model. The proposed model reduction approach does not require the parameters of individual IBRs and using standardized test data as input to the formulated optimization problem simplifies the reduced-order modelling scheme. Extensive case studies following standardized test scenarios verified the remarkable accuracy of the proposed approach.

Yallamilli, Ram S. [Purdue University]↗
DOE OSTI2021

Electron and photon reconstruction and identification with the CMS experiment at the CERN LHC

The performance is presented of the reconstruction and identification algorithms for electrons and photons with the CMS experiment at the LHC. The reported results are based on proton-proton collision data collected at a center-of-mass energy of 13 TeV and recorded in 2016–2018, corresponding to an integrated luminosity of 136 fb^-1. Results obtained from lead-lead collision data collected at √(sNN)=5.02 TeV are also presented. Innovative techniques are used to reconstruct the electron and photon signals in the detector and to optimize the energy resolution. Events with electrons and photons in the final state are used to measure the energy resolution and energy scale uncertainty in the recorded events. The measured energy resolution for electrons produced in Z boson decays in proton-proton collision data ranges from 2 to 5%, depending on electron pseudorapidity and energy loss through bremsstrahlung in the detector material. The energy scale in the same range of energies is measured with an uncertainty smaller than 0.1 (0.3)% in the barrel (endcap) region in proton-proton collisions and better than 1 (3)% in the barrel (endcap) region in heavy ion collisions. The timing resolution for electrons from Z boson decays with the full 2016–2018 proton-proton collision data set is measured to be 200 ps.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A Machine Learning Framework to Deconstruct the Primary Drivers for Electricity Market Price Events

As the electricity grid is moving towards a 100% Renewable Energy Source Bulk Power Grid, the overall operations of the power system operations and electricity markets are changing. The electricity markets are not only dispatching resources economically but also taking into account various controllable actions like renewable curtailment, transmission congestion mitigation, and energy storage optimization to make sure the grid is operating reliably. As a result, price formations in electricity markets have become quite complex. Traditional root cause analysis and statistical approaches are rendered inapplicable to analyze and infer the main drivers behind price formation in the modern grid and markets with variable renewable energy (VRE). In this paper, we propose a machine learning analysis framework to deconstruct some primary drivers for price formation in modern electricity markets with high renewable energy and the outcomes can be utilized for various critical aspects of market design, renewable dispatch and curtailment, operations, and cyber-security applications. The framework can be applied to any ISO or market data and in this paper it is applied to open-source publicly available datasets from California Independent System Operator (CAISO) and ISO New England.

machine learning (ML), electricity markets, Renewa↗
DOE OSTI2023

Hydropower Advantages over Batteries in Energy Storage of Off-Grid Systems: A Case Study

Microgrids are decentralized power production systems, where the energy production and consumption are very close to each other. Microgrids generally exploit renewable energy sources, encountering a problem of storage, as the power production from solar and wind is intermittent. This research presents a new integrated methodology and discusses a comparison of batteries and pumped storage hydropower (PSH) as energy storage systems with the integration of wind and solar PV energy sources, which are the major upcoming technologies in the renewable energy sector. We implemented the simulator and optimizer model (HOMER), which develops energy availability usage to obtain optimized renewable energy integration in the microgrid, showing its economic added value. Two scenarios are run with this model—one considers batteries as an energy storage technology and the other considers PSH—in order to obtain the best economic and technical results for the analyzed microgrid. The economic analysis showed a lower net present cost (NPC) and levelized cost of energy (LCOE) for the microgrid with PSH. The results showed that the microgrid with the storage of PSH was economical, with an NPC of 45.8 M€ and an LCOE of 0.379 €/kWh, in comparison with the scenario with batteries, which had an NPC of 95.2 M€ and an LCOE of 0.786 €/kWh. The role of storage was understood by differentiating the data into different seasons, using a Python model. Furthermore, a sensitivity analysis was conducted by varying the capital cost multiplier of solar PV and wind turbines to obtain the best optimal economic solutions.

Guruprasad, Prajwal↗
NASA NTRS2013

Designing the X-Ray Microcalorimeter Spectrometer for Optimal Science Return

Recent advances in X-ray microcalorimeters enable a wide range of possible focal plane designs for the X-ray Microcalorimeter Spectrometer (XMS) instrument on the future Advanced X-ray Spectroscopic Imaging Observatory (AXSIO) or X-ray Astrophysics Probe (XAP). Small pixel designs (75 microns) oversample a 5-10" PSF by a factor of 3-6 for a 10 m focal length, enabling observations at both high count rates and high energy resolution. Pixel designs utilizing multiple absorbers attached to single transition-edge sensors can extend the focal plane to cover a significantly larger field of view, albeit at a cost in maximum count rate and energy resolution. Optimizing the science return for a given cost and/or complexity is therefore a non-trivial calculation that includes consideration of issues such as the mission science drivers, likely targets, mirror size, and observing efficiency. We present a range of possible designs taking these factors into account and their impacts on the science return of future large effective-area X-ray spectroscopic missions.

X-rays↗
DOE OSTI2021

Dynamic Process Intensification via Data-Driven Dynamic Optimization: Concept and Application to Ternary Distillation

Process intensification is a design philosophy aimed at making chemical processes safer and more efficient. Its implementation often results in significant modifications to the design and structure of the process, with several conventional unit operations occurring in the same physical device. Traditionally, process intensification has focused on steady-state operation. In our previous works, we introduced dynamic process intensification (DPI) as a new intensification paradigm based on operational changes for conventional or intensified units. DPI is predicated on switching operation between two auxiliary steady states selected via a steady-state optimization calculation that ensures that the system generates, on average and over time, the same products as in nominal steady-state operation, but with favorable economics. This paper extends the DPI concept and introduces a novel dynamic optimization-based DPI strategy (Do-DPI) that involves imposing a true cyclic operation rather than switching between two discrete states. We discuss its implementation using surrogate dynamic models learned via system identification. Here, an extensive case study concerning a ternary distillation column separating a canonical hydrocarbon mixture shows that Do-DPI can reduce energy use by more than 4% relative to steady-state operation, with no significant deviations in product quality and production rate.

42 ENGINEERING↗
DOE OSTI2026

Convex Optimization with Smart Grid Examples

In this talk, we give an overview of the field of convex optimization and work through four canonical problems that relate to electrical power systems and smart grids. The purpose of these examples is to demonstrate the breadth of applications of convex optimization in energy research and to show that toy versions of these problems can be solved in just a few lines of code, indicating the scale and complexity of problems that can be tackled with a more detailed treatment. We emphasize the cvxpy modeling language as a foundational technology that enables rapid development and prototyping of convex optimization problems, allowing researchers to focus on model development rather than get caught in the weeds of numerical and code implementation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2019

Optimization of a Remote Sensing Energy Balance Method over Different Canopy Applied at Global Scale

Parameterization methods which calculate turbulent heat and water fluxes with thermal remote sensing data were evaluated in the revised remote sensing surface energy balance system (SEBS) model (Chen et al., 2013). The model calculates sensible heat (H) based on the Monin-Obukhov similarity theory (MOST) and determines latent heat (LE) as the residual of energy balance. We examined the uncertainties of H and LE in the SEBS model due to five key parameters at the local station point scale. Observations at 27 flux towers located in seven land cover types (needle-leaf forest, broad leaf forest, shrub, savanna, grassland, cropland, and sparsely vegetated land) and an artificial intelligence particle swarm optimization (PSO) algorithm was combined to calibrate the five parameters (leaf drag coefficient, leaf heat transfer coefficients, roughness length for soil, and two parameters for ground heat calculation) in the SEBS model. The root-mean-square error at the site scale was reduced by 9 W/sq.m for H, and 92 W/sq.m for LE, and their correlation coefficients were increased by 0.07 (H) and 0.11 (LE) after using the calibrated parameters. The updated model validation was further conducted globally for the remotely sensed evapotranspiration (ET) calculations. Overestimation of SEBS global ET was significantly improved by using the optimized values of the parameters. The results suggested PSO was able to consistently locate the global optimum of the SEBS model, and appears to be capable of solving the ET model optimization problem.

Chen, Xuelong↗
DOE OSTI2021

IEA Wind Energy Task 37 - System Engineering - Aerodynamic Optimization Case Study

This paper presents the results from the first IEA Wind Task 37 aerodynamic optimization case study. 8 participants applied their optimization tools to a purely aerodynamic problem and the results were compared. Overall, the different tools produced widely different designs, while there was better agreement in the improvement achieved. This highlights the fact that further investigation is needed to try to understand these differences and develop best practices. There were too many differences between the different analysis and optimization codes to determine the sources of these differences. However, several potential sources of discrepancy were identified for further investigation. One hypothesis is that one potential source of discrepancy is that the design problem itself is relatively flat in design directions of constant loading. This flatness would impact the convergence in the optimization, while at the same time mean that discrepancies in the design itself would be less severe.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2021

IEA Wind Energy Task 37 System Engineering Aerodynamic Optimization Case Study: Preprint

This paper presents the results from the first IEA Wind Task 37 aerodynamic optimization case study. Eight participants applied their optimization tools to a purely aerodynamic problem and the results were compared. Overall, the different tools produced widely different designs, while there was better agreement in the improvement achieved. This highlights the fact that further investigation is needed to try to understand these differences and develop best practices. There were too many differences between the different analysis and optimization codes to determine the sources of these differences. However, several potential sources of discrepancy were identified for further investigation. One hypothesis is that one potential source of discrepancy is that the design problem itself is relatively flat in design directions of constant loading. This flatness would impact the convergence in the optimization, and at the same time mean that discrepancies in the design itself would be less severe.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2025

RLGBS: Reinforcement Learning-Guided Beam Search for process optimization in a paper machine dryer section

Paper drying is responsible for over two-thirds of energy consumption in the U.S. pulp and paper industry, presenting significant potential for energy savings through optimization of process parameters. Current approaches often assume fixed operating conditions, neglecting dynamic ambient and process variations that limit achievable savings and real-world applicability. To this end, we develop a physics-based simulation environment for a paper machine dryer section and propose a reinforcement learning (RL) framework to minimize overall energy consumption by optimizing drying process parameters under diverse operating conditions. To mitigate overdrying and numerical instabilities caused by suboptimal local RL actions, we introduce Reinforcement Learning-Guided Beam Search (RLGBS), which explores multiple action sequences in parallel using beam search. Instead of making step-by-step decisions, RLGBS prioritizes solutions based on cumulative probability, reducing the impact of individual suboptimal actions. Experiments demonstrate that RLGBS achieves consistent energy savings under unseen operating conditions not encountered during training, outperforming conventional RL methods. While validated in drying optimization, this framework is broadly applicable to other RL-based industrial process control problems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Electricity Bill Calculator (elecprice) v0.1.0

The Electricity Bill Calculator Library is a generic tool for manipulating the tariffs of electricity, with an emphasis on commercial Time-Of-Use (TOU) rates in the U.S. and residential Net Energy Metering tariffs in CA. Typical uses of the package are price signal generation and bill computation. To generate price signals from a specific tariff and given a time window, the tool creates a pandas dataframes containing the various components of the electricity charges, at each time step. This is particularly useful for Demand Response (DR) applications, such as price-based optimization of energy in buildings. The tool also computes bills given a building's power consumption and a specific tariff and returning the corresponding cost of electricity, as well as a breakdown per type of rate.

Prakash, Anand Krishnan↗