SEARCH · Engineering Papers

Results for “Optimized Building Performance”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

All sources NASA NTRS DOE 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

BOPTest As a Platform for Building Controls and Grid-Interactive Buildings Workforce Training

Building automation and controls are becoming increasingly complex with the emergence of Grid Integrated Efficient Buildings (GEBs) as well as new highly efficient sequences of operation and data-driven control schemes. However, there remains a significant gap in hands-on training opportunities for building operators and technicians to gain practical experience with advanced control systems in a low-risk environment. This paper presents BOPTEST (Building Optimization Performance Test) as a suitable platform for workforce training in building controls and GEB technologies. BOPTEST provides a suite of standardized building simulation test cases with a REST API, real-time control interfaces through BACnet, semantic models connecting users to building data, and built-in calculation of control metrics and performance indicators. The platform enables trainees to interact with virtual buildings using industry-standard protocols while learning how to implement and innovate control strategies. The training platform is designed to offer a structured and interactive learning experience for building engineers, helping them effectively develop, learn, and retain skills in fault identification, troubleshooting, and correction. The workflow is divided into three main phases: 1) Setup, 2) Exercise, and 3) Review, each comprising specific activities performed by either the instructor or the student. Initial pilot training sessions have yielded positive feedback from instructors and participants and demonstrates that BOPTEST effectively fills an industry need for a low-risk training resource via simulation of real building control systems, allowing trainees to gain practical experience before working in the field. The platform's ability to provide immediate performance feedback while maintaining familiar industry interfaces makes it particularly suitable for workforce development programs. This work provides a replicable model for leveraging building simulation in control education and training.

Paul, Lazlo↗

DOE OSTI2025

BOPTEST as a Platform for Building Controls and Grid-Interactive Buildings Workforce Training

Paul, Lazlo↗

DOE OSTI2024

Cybersecurity Considerations and Research Pathways for Grid-Interactive Efficient Buildings

Federal facilities serve critical missions and functions that require safe, reliable, and efficient operations. Digitization of several facility operations has increased the cost-effectiveness of energy usage and optimization of energy system performance. As the building controls landscape shifts to become more connected and smarter, building operators now face unique opportunities and challenges to adopt smart enabled devices that can lower energy usage while also optimizing building system performance. The grid-interactive efficient buildings (GEB) initiative aims to make buildings cleaner and more flexible through these smart devices. Smart enabled devices allow greater connectivity and control through remote operations and provide crucial data for analytics and increased efficiency. GEBs enable demand flexibility that has the potential to reduce electrical costs and transform the grid edge where buildings connect to power grids. This operation of interconnected systems, if not designed with cybersecurity practices, causes security gaps and introduces potential attack paths by adversarial and non-adversarial entities leading to disruption of operations.

building controls↗

DOE OSTI2023

The application of EN ISO 52016-1 to assess building cost-optimal energy performance levels in Italy

Not Available

Bianco Mauthe Degerfeld, Franz↗

DOE OSTI2025

Comparative life cycle assessment of a modular cross-laminated timber residential building designed for disassembly and reuse versus traditional wood frame construction

There is a need for affordable housing across the U.S., with high-performance modular and prefabricated buildings providing a logical avenue for meeting some of this demand. However, there is a need to balance high performance construction – including low emissions – with affordability. To provide a proof-of-concept in meeting these goals, the Circular Home is a cross-laminated timber (CLT)-based deconstructible and reconfigurable single-family residence that meets high performance targets in moisture, energy, design, economics, and life cycle assessment (LCA). This study focuses on the LCA, presenting a cradle-to-cradle whole-building life cycle assessment (WBLCA) for the Circular Home and a functionally equivalent Baseline Home constructed with traditional materials and methods. The functional unit is 1 m 2 of gross floor area across 60 years. Revit building information models (BIM) provided material quantities and Tally LCA was utilized for impact data (inclusive of biogenic carbon sequestration), supplemented with manufacturer environmental product declarations (EPDs). The Circular Home outperforms the baseline residence in most measured impact categories, including global warming potential (GWP), producing −2.73 kgCO 2 eq/m 2 in embodied emissions, whereas the modeled baseline has an embodied GWP of 428 kgCO 2 eq/m 2 . The careful material selection and advanced building design optimizes performance, with the Circular Home containing only −0.006 times the embodied emissions and −0.02 times the operational emissions of its traditional counterpart. Finally, the unique contribution of this work is in the environmental impact comparison of a high-performance modular CLT structure that can be affordably scaled and mass produced in a U.S. market, compared to typical single family home construction.

Circularity↗

DOE OSTI2024

Defining weather scenarios for simulation-based assessment of thermal resilience of buildings under current and future climates: A case study in Brazil

In response to increasingly severe weather conditions, optimization of building performance and investment provides an opportunity to consider co-benefits of thermal resilience during energy efficiency retrofits. This work aims to assess thermal resilience of buildings using building performance simulation to evaluate the indoor overheating risk under nine weather scenarios, considering historical (2010s), mid-term future (2050s), and long-term future (2090s) typical meteorological years, and heat wave years. Such an analysis is based on resilience profiles that combine six integrated indicators. A case study with a district of 92 buildings in Brazil was conducted, and a combination of strategies to improve thermal resilience was identified. Results reflect the necessity of planning for resilience in the context of climate change. This is because strategies recommended under current conditions might not be ideal in the future. Therefore, an adaptable design should be prioritized. Cooling energy consumption could increase by 48 % by the 2050s, while excessive overheating issues could reach 37 % of the buildings. Simple passive strategies can significantly reduce the heat stress. A comprehensive thermal resilience analysis should ultimately be accompanied by a thorough reflection on the stakeholders’ objectives, available resources, and planning horizon, as well as the risks assumed for not being resilient.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Decarbonization Considerations: Grid-Interactive Efficient Buildings [Slides]

The Federal Energy Management Program (FEMP) is helping federal agencies understand how to meet decarbonization goals with grid interactive efficient buildings (GEB). This training will provide attendees with an introduction to GEB, how to work with utilities, and opportunities for federal sites.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Using the ATLAS experiment software on heterogeneous resources

With the large dataset expected from 2030 onwards by the HL-LHC at CERN, the ATLAS experiment is reaching the limits of the current data processing model in terms of traditional CPU resources based on x86_64 architectures and an extensive program for software upgrades towards the HL-LHC has been set up. The ARM CPU architecture is becoming a competitive and energy efficient alternative. Accelerators like GPUs are available in any recent HPC. In the past years ATLAS has successfully ported its full data processing and simulation software framework Athena to ARM and has invested significant effort in porting parts of the reconstruction and simulation algorithms to GPUs. We report on the successful usage of the ATLAS experiment offline and online software framework Athena on ARM and GPUs through the PanDA workflow management system at various WLCG sites. Furthermore we report on performance optimizations of the builds for ARM CPUs and the GPU integration efforts. We will discuss performance comparisons of different ARM and x86_64 architectures on WLCG resources and Cloud compute providers like GCP and AWS using ATLAS productions workflows as used in the Hep-Score23 benchmark suite.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Machine Learning-Driven Optimization of Building Enclosures for Moisture Durability and Thermal Performance

The design of moisture-durable building enclosures with low embodied carbon often involves an iterative process of selecting the materials for the specific exposure conditions to meet the performance requirements. While hygrothermal simulations are commonly used to evaluate moisture durability, they often require advanced expertise for proper implementation. Machine learning (ML) provides a promising alternative by streamlining the design process and minimizing the reliance on complex simulations. This study presents a machine learning-based approach for predicting moisture durability in residential wall assemblies. The ML model was trained to estimate the mold index and maximum moisture content of various layers under typical exposure conditions. The model achieved a high predictive accuracy, with a coefficient of determination (R²) exceeding 0.90 when compared to traditional hygrothermal simulations on materials that were not part of training the ML model. Building on these results, the ML model was developed into a practical tool for optimizing wall assembly designs. This tool allows users to automatically optimize material selections based on energy, moisture, and carbon performance criteria. By incorporating multi-objective optimization, the tool identifies configurations that minimize embodied carbon while maintaining moisture safety and code-compliant thermal performance. Additionally, it provides insights into how material choices influence assembly durability, energy efficiency, and carbon reduction. The tool will be implemented in the Building Science Advisor (BSA) to enhance its performance and provide more granularity on the results. This research highlights the potential for ML-driven tools to simplify the design of high-performance building enclosures, offering architects and engineers a faster, more efficient way to balance critical performance factors.

Salonvaara, Mikael [ORNL] (ORCID:0000000318991554)↗

DOE OSTI2022

Case Study: NREL Campus Chilled Water Storage Potential: Benchmark Datasets Development and Applications, Task 4 - Use Case Demonstration

The Benchmark Datasets Development and Applications project is a three-year collaboration between the National Renewable Energy Laboratory (NREL), Oak Ridge National Laboratory, Pacific Northwest National Laboratory, and Lawrence Berkeley National Laboratory. The project seeks to collect and curate high-resolution, well-calibrated time series of building operational and indoor/outdoor environmental data, which are crucial to understanding and optimizing building energy efficiency performance and demand flexibility capabilities as well as benchmarking energy algorithms. Project outcomes include approximately twelve high-fidelity building datasets, enhanced data representation tools, and four case studies to illustrate example applications. The goal of these case studies is to define and execute analyses that demonstrate how one or more datasets collected through this project can address a data gap or challenge historically faced by building stakeholders. This technical paper summarizes the findings of one of these case studies, in which we studied the operational efficiencies of the central cooling system at NREL. We looked at three years of data from the three chillers in the Field Test Laboratory Building (FTLB), from 2019 to 2021, to compare equipment operation and demand throughout the time period. Our analysis indicates that all three chillers are operating at or below the optimal loading conditions for most of the operation time, and thus there was no efficiency drop due to loading of the chillers at full capacity. Our recommendation is that no chiller capacity increase is needed; instead, the central plant could benefit from adopting advanced control logics for optimal sequencing of chillers during part load operations. Analysis of adding chilled water thermal storage to the central plant indicated 34% savings in demand cost and 24.5% savings in total cost (energy consumption and demand charge cost). The payback period is estimated to be 11-22 years with an assumed TES cost of $\$$100-$200 per ton. This case study shows how a selected dataset is used to solve a practical building problem - learning the operational status of its components, analyzing the effectiveness of a proposed new technique, and aiding decision-making for the building operations and maintenance team.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Reducing the Overnight Capital Cost of Advanced Reactors Using Equipment-Level Seismic Protective Systems

Consideration of the effects of earthquake shaking on the design and construction of nuclear power plants adds substantially to the overnight capital cost, with anecdotal estimates as high as 35+%, attributed to additional construction materials, need for one-off and sub-optimal designs of equipment due to conflicting design choices, the high cost of seismic qualification of equipment, and regulatory review. Safety-critical equipment in large light water reactors is designed and qualified for seismic demands imposed by the supporting reactor building, optimal mechanical designs are not possible, and designs of a given piece of equipment may vary with height above grade. Similar negative impacts are expected for advanced reactors unless the seismic design paradigm is changed. The overarching goal of this transformational MEITNER project, which involved a multidisciplinary engineering team and designers of three fundamentally different advanced reactors, was to adapt proven seismic isolation and damping technologies to operationalize modular protective systems for safety-class equipment inside advanced reactor buildings. Such seismic protective systems would be tightly integrated into design development for reactor support systems and balance-of-plant construction. The adoption of the technology, which is widely used in non-nuclear sectors, would simplify plant design, enable the use of standardized equipment and buildings, optimized for operational performance, and reduce plant size and weight. The need for site-specific equipment would be eliminated, enabling identical equipment to be used across multiple plants sited across the US and economies of scale, and catalyzing new interest and investment. The equipment-based protective systems would allow siting of advanced reactors in regions of high seismic hazard.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1981

Assessment of solar-assisted gas-fired heat pump systems

As a possible application for the Goldstone Energy Project, the performance of a 10 ton heat pump unit using a hybrid solar gas energy source was evaluated in an effort to optimize the solar collector size. The heat pump system is designed to provide all the cooling and/or heating requirements of a selected office building. The system performance is to be augmented in the heating mode by utilizing the waste heat from the power cycle. A simplified system analysis is described to assess and compute interrrelationships of the engine, heat pump, and solar and building performance parameters, and to optimize the solar concentrator/building area ratio for a minimum total system cost. In addition, four alternative heating cooling systems, commonly used for building comfort, are described; their costs are compared, and are found to be less competitive with the gas solar heat pump system at the projected solar equipment costs.

Lansing, F. L.↗

DOE OSTI2025

Automated model generation and parameter estimation of building energy models using an ontology-based framework

This study presents a methodology for automated model generation and parameter estimation of building energy models using semantic modeling and Bayesian estimation. Semantic modeling techniques are used to represent the system components and their interactions, facilitating the automatic generation of a simulation model from dynamic component models. The proposed approach is applied to a case study of a ventilation system where a simulation model is generated, calibrated, and assessed through different performance metrics. These metrics demonstrate the accuracy and reliability of both model point estimates and probabilistic prediction intervals across all model outputs. Overall, the proposed methodology offers a systematic and automated approach to model development and calibration in building energy systems, with potential applications in building performance analysis, monitoring, and optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

An open control sequence specification to scale building demand flexibility via analytics software

For over two decades, researchers and practitioners have showcased the ability of large commercial buildings to provide grid services by shedding or shifting load. Various utility demand response (DR) and virtual power plant (VPP) programs throughout the United States are presently utilizing these demand-side resources. However, growth of these programs have been limited, in part due to the high cost necessary to integrate the DR control strategies into the building automation system (BAS). Implementing these strategies involves adjusting control sequences, necessitating dozens of hours of customized programming per building, limiting their adoption to large organizations and progressive owners. Recent efforts by researchers and industry have demonstrated the capability of energy management and information systems (EMIS), originally designed for fault detection and diagnostics, to interface with existing BAS and perform supervisory control to optimize building operations. While these approaches are quickly being adopted by industry, demand flexibility (DF) control strategies remain limited in product offerings. One of the challenges is the lack of documented best-practice DF sequences, despite the rich literature on field implementations. This paper develops a new open-specification for a zone-based temperature adjustment shed strategy for commercial building HVAC systems, describing the specification’s implementation in two EMIS tools in both experimental and field settings. Both implementations successfully reduced electric load by at least 40% on average during the called event, while maintaining temperature limits. This study’s detailed process from specification to deployment shows the potential for scalability as well as highlights challenges related to integration with heterogeneous BAS products.

Granderson, Jessica↗

NASA NTRSDate not supplied

Design Concepts for an Optimized, Modular, and Scalable Liquid Amine Test Stand

The Air Revitalization Labs at NASA Ames Research Center (ARC) is investigating liquid amines to for their performance removing spacecraft carbon dioxide (CO2) for crewed space missions. Development of the current one-crew scale amine test stand stems from several modifications to a test stand initially built at NASA Johnson Space Center (JSC) This sub-scale system has been modified to incorporate a flow spreader for the inlet air stream, an updated contactor design for CO2 capture, a degasser to regenerate the liquid sorbent and recover the captured CO2, and a condenser to reduce water loss. Results from the existing integrated liquid amine test stand have provided valuable insight, but continued performance optimization requires design and build of a new integrated test system. New design concepts will institute a modular configuration to allow for interfacing with novel contactor and degasser architecture, parallel or series flow pathways for the air stream and liquid sorbent, and scaling up to a 4-crew CO2 removal system.

Tiago Faria Costa↗

NASA NTRS2012

Performance Assessment of Baseline Cells for the High Efficiency Space Power Systems Project

The Enabling Technology Development and Demonstration (ETDD) Program High Efficiency Space Power Systems (HESPS) Project, formerly the Exploration Technology Development Program (ETDP) Energy Storage Project is tasked with developing advanced lithium-ion cells for future NASA Exploration missions. Under this project, components under development via various in-house and contracted efforts are delivered to Saft America for scale-up and integration into cells. Progress toward meeting project goals will be measured by comparing the performance to these cells with cells of a similar format with Saft s state-of-the-art aerospace chemistry. This report discusses the results of testing performed on the first set of baseline cells delivered by Saft to the NASA Glenn Research Center. This build is a cylindrical "DD" geometry with a 10 Ah nameplate capacity. Testing is being performed to establish baseline cell performance at conditions relevant to ETDD HESPS Battery Key Performance Parameter (KPP) goals including various temperatures, rates, and cycle life conditions. Data obtained from these cells will serve as a performance baseline for future cell builds containing optimized ETDD HESPSdeveloped materials. A test plan for these cells was developed to measure cell performance against the high energy cell KPP goals. The goal for cell-level specific energy of the high energy technology is 180 Wh/kg at a C/10 discharge rate and 0 C. The cells should operate for at least 2000 cycles at 100 percent DOD with 80 percent capacity retention. Baseline DD cells delivered 152 Wh/kg at 20 C. This number decreased to 143.9 Wh/kg with a 0 C discharge. This report provides performance data and summarizes results of the testing performed on the DD cells.

Schneidegger, Brianne T.↗

DOE OSTI2024

Large-scale simulation-based parametric analysis of an optimal precooling strategy for demand flexibility in a commercial office building

Achieving success with grid-interactive efficient buildings (GEBs) is closely tied to the utilization of flexible loads. A valuable strategy involves the implementation of precooling techniques before high-demand events, such as peak hours, by adjusting zone air temperature setpoints. This leads to a reduction in thermal loads and peak electricity demand during these times, as the building’s thermal mass stores and subsequently releases thermal energy. However, the effectiveness of the pre-cooling optimization is highly contingent on specific conditions such as building thermal properties, weather conditions, utility rate structure, HVAC equipment sizing, etc. Therefore, investigating the impacts of these condition-specific factors is crucial, especially when considering precooling strategies that utilize thermal mass in commercial buildings. In this paper, we first devised a novel heuristic control approach that incorporates parameterized optimal precooling thermostat schedules to enhance demand flexibility in a commercial office building. Subsequently, we conducted a thorough performance evaluation of this control strategy. Here, the optimal thermostat schedule was parameterized using three optimization variables: the precooling start time, the precooling end time, and the precooling temperature setpoint. Utilizing the DOE medium-sized office building as the virtual testbed, we showed that the parameterized schedule effectively approximates model predictive control and requires drastically reduced computational overhead. In addition, we investigated the impact of different influencing factors on the optimal precooling strategy. These factors include building thermal mass, outdoor air conditions, and energy price profiles. Using high-performance computing, we simulated a total of 225 scenarios, consisting of three levels of thermal mass, five typical outdoor air temperature profiles, and fifteen time-of-use price plans. The results demonstrate that optimal thermostat scheduling could save substantial energy cost in medium-sized office buildings with heavy thermal mass but with some energy penalty. Although the potential for cost savings is lower in buildings with low and medium thermal mass, the energy penalty remains consistent in all three thermal mass scenarios. The study also highlights the need to account for zone diversity and recognize that a one-size-fits-all-zone setpoint schedule may not be suitable for all zones and can lead to unnecessary energy wastage. Furthermore, the results highlight that while outdoor air conditions play a role in cost and energy performance, the cooling load exerts a more immediate and substantial influence on cost savings in precooling strategies. Although cost savings are comparable under certain conditions with the same cooling load, observed deviations in energy penalty indicate potential disparities in the efficiency of the HVAC system during the load-shifting process. In addition, the duration of peak pricing and the ratio between peak and off-peak times exhibit clear correlations with cost savings and energy consumption, aligning with intuitive expectations. These findings offer valuable insights for optimizing precooling strategies in office buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗