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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Optimizing Heat Recovery with Storage: Control Validation and Sensitivity Analysis of the Time-Independent Energy Recovery Plant Using Modelica

Heat recovery in large building central plants saves energy but traditionally requires simultaneous heating and cooling. The Time-Independent Energy Recovery (TIER) plant shifts this paradigm by integrating thermal energy storage (TES) to enable heat recovery regardless of concurrent demand, offering a highly efficient, space-saving solution to achieve California’s energy goals. However, its integration of heat recovery chillers, cooling-only chillers, cooling towers, and trim air-source heat pumps (ASHPs) creates growing control and sizing complexity. To overcome this, this study employs high-fidelity Modelica dynamic simulation to validate TIER control sequences and optimize equipment sizing. We translated the written Sequences of Operation into executable Control Description Language (CDL) to test logic against sub-hourly loads. This verification workflow successfully identified and resolved critical vulnerabilities, such as thermal storage freezing and equipment short-cycling, in a virtual environment prior to physical deployment. Then, the study analyzes TIER plant performance across three simulated building types in three locations, and a real building load profile, ensuring variety in heating and cooling loads, and simultaneity factors and explores sizing rules for the TES and ASHP capacity. The analysis shows that the TIER plant operates equipment efficiently leading to a plant SCOP of around 7.5 across all scenarios, higher than a traditional ASHP plant, and a viable pathway to de-risk complex system design and control through simulation to identify optimal designs that maximize energy efficiency, minimize operational costs, and ensure robust operation in varied environmental conditions, thereby facilitating the broader adoption of such a solution for large buildings.

Zanetti, Ettore↗
DOE OSTI2026

An Online Tool for Preliminary Design and Techno-Economic Analysis of District Geothermal Heating and Cooling Systems

District geothermal heating and cooling systems (DGHCS) have significant benefits for reducing energy consumption as well as building- and grid-level peak electric demand. Currently, no publicly available tools are available to effectively design and conduct techno-economic analysis of DGHCS. GeoWISE was originally developed for preliminary design and techno-economic analysis of geothermal heating and cooling systems in an individual commercial or residential building. This paper introduces recent upgrades of GeoWISE that allow users to design and conduct techno-economic analysis of DGHCS. Several new features are implemented in GeoWISE to allow selection and specification of multiple new or existing buildings. A database of information for over 125 million existing U.S. buildings was used in GeoWISE that allows users easily locate existing buildings of interest based on street addresses, and optionally edit information of the buildings (e.g., footprint, vintage, principal functions, number of floors, window-to-wall ratio). Unique energy simulation models of the selected buildings are then automatically created using the Automatic Building Energy Modeling (AutoBEM) and EnergyPlus simulations are performed to predict thermal loads of the buildings. A simplified DGHCS is then designed and simulated to predict its energy use. A central borehole heat exchanger (BHE) of the DGHCS is sized using the RowWise algorithm of GHEDesigner to meet the thermal loads within user-specified land areas for installing BHE. The upgraded GeoWISE reports the needed capacity of heating and cooling equipment in each building, design of the central BHE, energy consumption reduction, and energy cost saving resulting from using DGHCS compared with conventional HVAC systems. A case study is showcased using the upgraded GeoWISE to design and conduct techno-economic analysis of a simplified DGHCS.

Prem Anand Jayaprabha, Jyothis Anand [ORNL] (ORCID↗
DOE OSTI2025

CityLearn v2: energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities

As more distributed energy resources become part of the demand-side infrastructure, quantifying their energy flexibility on a community scale is crucial. CityLearn v1 provided an environment for benchmarking control algorithms. However, there is no standardized environment utilizing realistic building-stock datasets for distributed energy resource control benchmarking without co-simulation or third-party frameworks. CityLearn v2 extends CityLearn v1 by providing a stand-alone simulation environment that leverages the End-Use Load Profiles for the U.S. Building Stock dataset to create grid-interactive communities for resilient, multi-agent, and objective control of distributed energy resources with dynamic occupant feedback. While the v1 environment used pre-simulated building thermal loads, the v2 environment uses data-driven thermal dynamics and eliminates the need for co-simulation with building energy performance software. This work details the v2 environment and provides application examples that use reinforcement learning control to manage battery energy storage system, vehicle-to-grid control, and thermal comfort during heat pump power modulation.

Nweye, Kingsley↗
DOE OSTI2021

Selecting durable building envelope systems with machine learning assisted hygrothermal simulations database

Hygrothermal simulations provide insight into the energy performance and moisture durability of building envelope components under dynamic conditions. The inputs required for hygrothermal simulations are extensive, and carrying out simulations and analyses requires expert knowledge. An expert system, the Building Science Advisor (BSA), has been developed to predict the performance and select the energy-efficient and durable building envelope systems for different climates. The BSA consists of decision rules based on expert opinions and thousands of parametric simulation results for selected wall systems. The number of potential wall systems results in millions, too many to simulate all of them. We present how machine learning can help predict durability data, such as mold growth, while minimizing the number of simulations needed to run. The simulation results are used for training and validation of machine learning tools for predicting wall durability. We tested Artificial Neural Network (ANN) and Gradient Boosted Decision Trees (GBDT) for their applicability and model accuracy. Models developed with both methods showed adequate prediction performance (root mean square error of 0.195 and 0.209, respectively). Finally, we introduce how the information supports guidance for envelope design via an easy-to-use web-based tool that does not require the end-user to run hygrothermal simulations.

Salonvaara, Mikael↗
DOE OSTI2024

Open-cycle thermochemical energy storage for building space heating: Practical system configurations and effective energy density

Salt-hydrate thermochemical materials (TCM) are promising candidates for energy storage systems for building space heating due to their high theoretical energy density and the need for low regeneration temperature. However, water vapor is required to drive the hydration process of the TCM reactor, which poses a challenge during winter when water vapor is typically scarce. Using indoor air directly lowers the building's humidity to an unconformable level in practice, while the cold outdoor air contains limited moisture. Here we consider different integration strategies for open-cycle TCM reactors in buildings and develop a model to simulate their thermal performance across diverse buildings and climates, specifically for building space heating. The potential energy densities and the levelized cost of storage of the TCM reactor are evaluated in practical scenarios to demonstrate the load-shifting potential of TCM systems for heating applications. We use a strontium chloride (SrCl 2 )-based composite as the baseline and explore the impact of various reactor and material changes to the energy density and levelized cost of storage.

25 ENERGY STORAGE↗
DOE OSTI2023

ResStock: Annual Baseline Results with Component Loads

The ResStock Analysis Tool was developed by NREL with support from the U.S. Department of Energy to provide a new approach to large-scale residential analysis by combining large public and private data sources, statistical sampling, detailed sub hourly building simulations, and high-performance computing. This combination achieves unprecedented granularity and accuracy in modeling the diversity of the housing stock and the distributional impacts of building technologies in different communities. The annual baseline energy results from a national-scale ResStock run use typical meteorological year 3 (TMY3) files for energy simulations. Results include heating and cooling loads for individual components of each building. Component loads describe the heating/cooling load that can be attributed to specific elements of a home, such as heat transfer through walls or internal gains. Additionally, these results include the standard ResStock outputs for housing characteristics and numerous energy outputs by end-use and fuel. A snapshot of the ResStock version used to produce this data, including a configuration file for the run can be found using the Source Code resource link.

Array↗
NASA NTRS2024

Configuring and Testing Mesh Radios for Air-To-Ground Communications

The initial mesh network used to demonstrate a simple mesh network for the air-to-ground challenge will consist of 4 mesh radios purchased from DoodleLabs. The multiband radios operate in both the 915MHz and 2450MHz frequencies and can use Wi-Fi to connect to deployed devices. The DoodleLabs radios come preconfigured with unique IP addresses but to make sure of compatibility each radio will be assigned an IP address. For initial testing configurations will be changed using the built-in local web server interface that DoodleLabs radios provide. To access the webserver a computer connects to the radios broadcast Wi-Fi network using the default credentials, then enter the default IP address into a browser. This webserver will allow the user to monitor the radio performance and make changes to the various systems. The simple configuration page will allow an operator to make many of the initial changes to place each radio on the network and secure each connection with a new password. Further testing will then be performed by building out a simulated virtual network of 26 nodes and connecting the 4 DoodleLabs radios into this simulation. This will give insight into the radio’s performance in the larger system they will likely operate in given the project requirements. This testing will focus on multi-hop throughput, latency and the resiliency to packet loss.

Mesh Radio↗
DOE OSTI2024

Towards in-situ certification of additively manufactured parts: the vital roles of physics-based and data-driven models

Certifying additively manufactured (AM) parts in-situ at the completion of a build is an enticing prospect, as it can help reduce the high costs associated with post-build testing and evaluation. However, achieving this goal presents significant challenges that may keep it aspirational for the foreseeable future. Nonetheless, incremental progress can pave the way forward. A critical aspect of in-situ certification involves continuous quality checking due to the random nature of the AM process and the difficulties in detecting defects or anomalies once layers are built over. While real-time in-situ monitoring strategies assisted by machine learning (ML) play a pivotal role in auditing part quality, they must ideally be supported by real-time (or near real-time) adaptive process control enabled by ML-assisted decision-making. By analyzing in-situ monitoring data in real-time (or near real- time) to dynamically adjust manufacturing parameters, such intervention can ensure AM parts are built to meet stringent certification standards. This can be achieved virtually by using high-fidelity performance models for the physical testing and evaluation tasks. In this short editorial, we discuss the key contributions made by data-driven and physics-based models in providing intelligence to the monitoring and process control tasks underpinning in-situ certification and in the simulation of the build’s performance under test and service conditions. While our focus lies in metal AM, the concepts discussed here are also relevant to other AM processes.

: In-situ monitoring↗
DOE OSTI2023

BuildStockQuery [SWR-23-58]

BuildStockQuery is a python library designed to simplify and streamline the process of querying massive, terabyte-scale datasets generated by ResStock(TM). ResStock (SWR-19-15) is a U.S. DOE-supported, NREL-built, national residential building energy stock model that enables a new approach to large-scale residential energy analysis across the U.S. by combining large public and private data sources, statistical sampling, detailed sub-hourly building simulations, and high-performance computing. BuildStockQuery offers an intuitive Object-Oriented Programming (OOP) interface to the ResStock output dataset allowing users to easily perform common queries and receive results in familiar pandas DataFrame format, abstracting away the need for complex SQL query. By initializing a query object with the pertinent Athena database and table names, users can easily query for various kinds of insights, for example, timeseries electricity for an end use for a given state grouped by building types.

Adhikari, Rajendra↗
DOE OSTI2025

Theory and simulations of cross-beam energy transfer between speckled laser beams

In this paper, we introduce a realistic modeling of laser beams smoothed by random phase plates to investigate cross-beam energy transfer (CBET). We compute the total field of the smoothed laser beams, which allows us to perform accurate simulations and to build a model accounting for the realistic structure of the speckles. This lets us confirm the results already discussed in a previous work given by Oudin et al. [Phys. Plasmas 29, 112112 (2022)]. When CBET is induced by a plasma flow, plane wave models can predict the exchange between smoothed laser beams. By contrast, when the exchange is caused by a wavelength shift between the laser fields of each beam, plane wave models overestimate the energy transfer, even for strongly Landau-damped ion acoustic waves. We also show that the laser angular spread, which results from its focusing, affects the resonance between the ponderomotive force induced by the laser fields and the ion acoustic wave. It increases the resonance width, which weakly depends on the Landau damping rate when there is a wavelength shift and no flow. In addition, the power transfer obtained with or without a phase plate is essentially the same in the perturbative regime and for small crossing angles.

Laser plasma interactions↗
DOE OSTI2022

Data-Enabled Predictive Control for Building HVAC Systems

Model predictive control is widely used as a control technology for the computation of optimal control inputs of building heating, ventilating, and air conditioning (HVAC) systems. However, both the benefits and widespread adoption of model predictive control (MPC) are hindered by the effort of model creation, calibration, and accuracy of the predictions. In this paper, we apply the data-enabled predictive control (DeePC) algorithm for designing controls for building HVAC systems. The algorithm solely depends on input/output data from the system to predict future state trajectories without the need for system identification. The algorithm relies on the idea that a vector space of all input–output trajectories of a discrete-time linear time-invariant (LTI) system is spanned by time-shifts of a single measured trajectory, given the input signal is persistently exciting. Closed-loop simulations using EnergyPlus are performed to demonstrate the approach. The simulated building modeled in EnergyPlus is a modified commercial large office prototype building served by an air handling unit-variable air volume HVAC system. Temperature setpoints of zones are used as control variables to minimize the HVAC energy cost of the building considering a time-of-use electricity rate structure. Furthermore, sensitivity analysis is conducted to gain insights into the effect of parameter tuning on DeePC performance. Simulation results are used to illustrate the performance of the algorithm and compare the algorithm with model-based MPC and occupancy-based setpoint controller. Overall, DeePC achieves similar performance compared to MPC for lower engineering effort.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Long-Term Assessment of Commercial Building Energy and Carbon Emissions in the Northwestern Region Under Future Weather Trend

The future climate significantly impacts building performance and increases uncertainties in energy simulations. A rising temperature trend is expected to heighten cooling loads during summer and result in more carbon emissions. Understanding the impact of future climate on building performance is significant for policymakers to make informed decisions. Building retrofit measures can improve building energy efficiency and reduce operational carbon emissions, yet their effects under future climate conditions have not been fully investigated so far. Thus, we proposed an assessment methodology for evaluating long-term energy consumption and operational carbon reduction potential using a building stock dataset. For this study, commercial buildings in the northwestern (NW) region were utilized to assess the impacts of future climate and building retrofit. In addition, we selected Montana with a cold and dry climate as an example to analyze and discuss the carbon emission reduction potential in buildings. The main findings are: (1) Under future climate trends, changes in energy use intensity (EUI) will fluctuate due to variations in heating and cooling degree-days (HDDs and CDDs) and increasing HDDs will lead to increasing EUI. (2) After applying annual building retrofitting, the long-term EUI reduction potential of buildings in the NW region will decrease with the increasing retrofitting degree, and the short-term EUI reduction potential will be impacted by the change of heating and cooling degree days. (3) In Montana, the long-term carbon intensity reduction potential of retrofitted buildings will decrease under future climate trends with the increasing renewable energy penetration.

building energy modeling↗
DOE OSTI2024

Performance assessment of near-fault buildings subjected to physics-based simulated earthquake ground motions with fling step

The effects of the co-seismic static offset (known as fling step) and associated velocity pulses on civil structures have been difficult to study because the static offset is typically removed during the processing of earthquake ground motion records. Simulated ground motions contain fling features and require no processing; therefore, they create new opportunities for representing fling features in seismic hazard analysis and assessing their influence on the seismic demands on near-fault structures. We use physics-based fault rupture simulations to study the characteristics of ground motions with fling step and the sensitivity of the near-fault structural demands to strong fling features. We uncover that simulated ground motions with a large fling step tend to have higher spectral intensity than those without a fling step at the same rupture distance, especially at periods longer than 2 s. As a result, the structural demands on flexible buildings tend to be the most sensitive to the fling features. Statistical analysis suggests that the ground motion spectral shape (represented by spectral accelerations at multiple periods) is—in most cases—a sufficient predictor of the structural demands on near-fault low-rise and mid-rise buildings at locations that are susceptible to strong fling effects. Finally, ground motion record selection experiments reveal that representing the spectral shape features at periods that are most relevant to a given structure may be an effective strategy to reduce the bias in the estimated demands on near-fault long-period structures when the available database of records is considered deficient in fling features.

Fling step↗
DOE OSTI2024

Commercial Building Prototypes Based on ANSI/ASHRAE/IES Standard 90.1-2019 Appendix G PRM: Technical Support Document

The two paths for documenting compliance with ANSI/ASHRAE/IES Standard 90.1 are the prescriptive path and the performance path. Beyond code programs and rating systems (for example, USGBC-LEED ) are primarily known to use a third path – the Appendix G Performance Rating Method. An update in the 2016 edition of Standard 90.1 approved the Appendix G Performance Rating System for code compliance, extending its application and allowing for greater consistency of modeling rules for code and beyond code building energy modeling. The Appendix G PRM provides rules for the development of whole building energy models of baseline and proposed models for calculating the “performance cost index target” value using the simulated energy results of the baseline and proposed models and the building performance factors published in Table 4.2.1.1 of the Standard. This report documents (1) the methodology used for development of the baseline and proposed energy models of the Pacific Northwest National Laboratory and U.S. Department of Energy commercial building prototypes using the Appendix G Performance Rating Method; and (2) the building performance factors that were calculated using those models.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1998

Modeling, Simulation and Analysis of Public Key Infrastructure

Security is an essential part of network communication. The advances in cryptography have provided solutions to many of the network security requirements. Public Key Infrastructure (PKI) is the foundation of the cryptography applications. The main objective of this research is to design a model to simulate a reliable, scalable, manageable, and high-performance public key infrastructure. We build a model to simulate the NASA public key infrastructure by using SimProcess and MatLab Software. The simulation is from top level all the way down to the computation needed for encryption, decryption, digital signature, and secure web server. The application of secure web server could be utilized in wireless communications. The results of the simulation are analyzed and confirmed by using queueing theory.

Liu, Yuan-Kwei↗
DOE OSTI2023

Empirical validation of building energy simulation model input parameter for multizone commercial building during the cooling season

This paper presents a critical advancement in Building Energy Modeling (BEM) through an empirical validation approach using a high-quality dataset from a multizone commercial office building in Oak Ridge, TN, USA. BEM is widely utilized in diverse construction applications, but its effectiveness relies on the accuracy of its predictions. The study focuses on empirical validation of input parameters in BEM, including building envelope data, infiltration modeling, and rooftop unit system performance curves. The validation of simulation input parameters leads to substantial improvements in the accuracy of simulation results. Notable both NMBE and cv (RMSE) values are reduced by 0.5 % for indoor air temperature and 17 % for indoor air relative humidity compared to the previous model. At the system level, both NMBE and cv (RMSE) values are reduced by 2 % for fan energy consumption and 4 % for cooling energy consumption, compared to the previous model. A literature review highlights a significant gap in empirical validation studies, which predominantly concentrate on either component-level or whole building validation. Furthermore, many studies employ simplified setups that may not faithfully represent the complexities of multizone commercial buildings. This paper distinguishes itself by emphasizing the critical importance of component-level input parameter validation. It underlines the need to validate data related to building envelope components and HVAC system performance curves, resulting in more accurate simulation outcomes. In conclusion, the utilization of actual multizone commercial building data enhances the study's practical relevance. In summary, this research underscores the pivotal role of input parameter validation in enhancing the accuracy and reliability of BEM.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Tailoring material microstructure and property in wire-laser directed energy deposition through a wiggle deposition strategy

Developing effective strategies to directly control material microstructure, property, and anisotropy is an active research area in metal additive manufacturing. This work develops a wiggle deposition pattern for wire-laser directed energy deposition (DED) of 316L stainless steel (SS) to modify the solidification texture, particularly in the building direction, in as-deposited samples. Through multi-physics simulation, operando near-infrared imaging, and synchrotron x-ray characterization, it is found that the wiggle deposition strategy induces highly dynamic melt flow and oscillating thermal gradient in the melt pool, which is responsible for the variation of preferable grain growth direction and crystallographic texture in the sample. The specific texture reduces the anisotropy in the tensile strength of as-printed 316L SS samples cut along different directions. Also, it largely increases the ductility along the build direction. Crystal plasticity simulation is performed to correlate the sample texture with mechanical property. In conclusion, this work offers a unique approach for tailoring local properties through the control of melt pool instability by applying different tool paths.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantum simulations for strong-field QED

Quantum field theory in the presence of strong background fields contains interesting problems where quantum computers may someday provide a valuable computational resource. In the noisy intermediate-scale quantum era it is useful to consider simpler benchmark problems in order to develop feasible approaches, identify critical limitations of current hardware, and build new simulation tools. Here we perform quantum simulations of strong-field QED (SFQED) in 3 + 1 dimensions, using real-time nonlinear Breit-Wheeler pair production as a prototypical process. The strong-field QED Hamiltonian is derived and truncated in the Furry-Volkov mode expansion, and the interactions relevant for Breit-Wheeler are transformed into a quantum circuit. Quantum simulations of a “null double slit” experiment are found to agree well with classical simulations following the application of various error mitigation strategies, including an asymmetric depolarization algorithm which we develop and adapt to the case of Trotterization with a time-dependent Hamiltonian. We also discuss longer-term goals for the quantum simulation of SFQED. Published by the American Physical Society 2024

Astronomy & Astrophysics↗