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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Lawrence Berkley National Laboratory Building 59 (Raw)

The building management system in Building 59 is monitoring and archiving building-level electricity usage, HVAC and lighting system states (e.g., setpoint, temperature, flow rate, pressure), indoor environmental conditions (air temperature, relative humidity, CO2), on-site weather (air temperature, relative humidity), and especially occupant counts as well as other metrics such as Wi-Fi signal. This dataset could support multiple use cases, such as model predictive control and occupant related demand management. Raw data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Lawrence Berkeley National Lab Building 59

The building management system in Building 59 is monitoring and archiving building-level electricity usage, HVAC and lighting system states (e.g., setpoint, temperature, flow rate, pressure), indoor environmental conditions (air temperature, relative humidity, CO2), on-site weather (air temperature, relative humidity), and especially occupant counts as well as other metrics such as Wi-Fi signal. This dataset could support multiple use cases, such as model predictive control and occupant related demand management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

System and method for occupancy-driven register airflow control

An HVAC register airflow control system and an air flow control method are provided. A housing of the system is in fluid communication with an air source for supplying an airflow. The housing includes an air outlet to the enclosed space. A detection sensor detects occupancy information of the enclosed space. A controller generates a control signal based on the occupancy information and controls the shape change of a damper made of a shape memory material. The damper is controlled to switch between a first operative configuration for preventing the airflow from entering the enclosed space and a second operative configured for permitting the airflow to enter the enclosed space.

Wang, Ya↗
DOE OSTI2023

Laboratory testing methods to evaluate the reliability of occupancy sensors for commercial building applications

The energy performance of commercial buildings is greatly influenced by occupants which are highly variable and among the most unpredictable components of a building's operation. While most building control systems use fixed, predetermined occupancy schedules, these fixed occupancy levels can be quite different from actual occupancy. This can cause unnecessary energy consumption, particularly from heating, ventilation, and air conditioning (HVAC) and lighting systems which are responsible for approximately 60% of commercial buildings' energy use. The use of occupancy counting sensor systems integrated with building management system controls is one method that can be used to improve the energy-consuming performance of buildings. However, there is no standardized universal methodology and metrics to evaluate their reliability. The aim of this research is to develop a uniform evaluation methodology to assess the reliability of occupancy counting sensor systems in a controlled laboratory environment. The developed testing methodology includes both “typical” scenarios representing the occupancy scenarios of a typical commercial building, and “failure” testing scenarios which represent a range of potential scenarios that may impact a sensor system's reliability. These methods were then implemented in a case study to evaluate the performance of two novel occupancy counting sensor systems (i.e., door-centric, and camera-based). Results suggest that typical testing results can be used to compare the overall performance of the occupancy counting sensor systems; however, failure testing is also important to understand the weaknesses of the sensor system in order to select the suitable one for the intended use of the commercial building. In addition, the proposed methodology includes a modified confusion matrix which enables the ability to identify if failures are caused by over or under counting occupants and to what extent this occurs over the testing period.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Getting Beyond Widgets: Performance of Efficient Indoor Air Quality System Retrofit Packages for Schools A report on the modeled energy, greenhouse gas, and cost savings of several multi-measure retrofit packages for energy efficiency and indoor air quality in primary schools

School facilities are often underfunded with aging and poorly maintained HVAC and lighting systems. Most existing school buildings stand to benefit significantly from retrofits in terms of energy, cost, and emissions savings. Ventilation and indoor air quality (IAQ), which are important aspects of a healthy and productive learning environment, can also be enhanced by some energy efficiency measures (EEMs). Packaging energy efficiency and IAQ systems retrofits may represent a golden opportunity to improve performance in this critical building sector.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Creating the Environment for Exploration Habitats

The Crew and Thermal Systems Division’s (CTSD) 20 Foot Chamber has undergone significant modifications to support NASA’s future human exploration missions to the Moon, Mars, and beyond. Existing chamber systems such as Vacuum/Repress, Heating Ventilation and Air Conditioning (HVAC), and Fire Suppression System (FSS), were upgraded, while new systems such as Air Revitalization and Gas Distribution were added. In addition, the chamber was outfitted with crew quarters, hygiene areas, storage, and workspaces. Teams across the Johnson Space Center (JSC) worked together to overcome the logistical and operational challenges of the planned test parameters. The ultimate goal was to create an analog testbed in which a maximum of 8 human test subjects could safely live and work for at least 11 days in the same conditions (reduced pressures, Oxygen concentrations, etc.) as those expected inside a base spacecraft. This would allow researchers to study the effects of such environments on humans and to validate proposed Prebreathe Protocols to enable the safe performance of surface extravehicular activities (EVAs). Over the last eighteen months, the CTSD Systems Test Branch has performed six tests of varying lengths and atmospheres for both NASA and commercial partners. To date, researchers now have collected data on 48 test subjects in the course of 42 days and over 130 simulated EVAs. This paper will discuss the history of the 20 Foot Chamber, its long road to becoming an analog testbed for human exploration, and the capabilities that make it a unique, world class facility for NASA and commercial human exploration missions. It will provide an overview of past and future testing, and the lessons learned along the way.

Cristina Aurora Anchondo↗
NASA NTRSDate not supplied

Creating the Environment for Exploration Habitats

The Crew and Thermal Systems Division’s (CTSD) 20 Foot Chamber has undergone significant modifications to support NASA’s future human exploration missions to the Moon, Mars, and beyond. Existing chamber systems such as Vacuum/Repress, Heating Ventilation and Air Conditioning (HVAC), and Fire Suppression System (FSS), were upgraded, while new systems such as Air Revitalization and Gas Distribution were added. In addition, the chamber was outfitted with crew quarters, hygiene areas, storage, and workspaces. Teams across the Johnson Space Center (JSC) worked together to overcome the logistical and operational challenges of the planned test parameters. The ultimate goal was to create an analog testbed in which a maximum of 8 human test subjects could safely live and work for at least 11 days in the same conditions (reduced pressures, Oxygen concentrations, etc.) as those expected inside a base spacecraft. This would allow researchers to study the effects of such environments on humans and to validate proposed Prebreathe Protocols to enable the safe performance of surface extravehicular activities (EVAs). Over the last eighteen months, the CTSD Systems Test Branch has performed six tests of varying lengths and atmospheres for both NASA and commercial partners. To date, researchers now have collected data on 48 test subjects in the course of 42 days and over 130 simulated EVAs. This paper will discuss the history of the 20 Foot Chamber, its long road to becoming an analog testbed for human exploration, and the capabilities that make it a unique, world class facility for NASA and commercial human exploration missions. It will provide an overview of past and future testing, and the lessons learned along the way.

Cristina A Anchondo↗
NASA NTRS2024

Creating the Test Environment for Exploration Habitats

The Crew and Thermal Systems Division’s (CTSD) 20 Foot Chamber has undergone significant modifications to support NASA’s future human exploration missions to the Moon, Mars, and beyond. Existing chamber systems such as Vacuum/Repress, Heating Ventilation and Air Conditioning (HVAC), and Fire Suppression System (FSS), were upgraded, while new systems such as Air Revitalization and Gas Distribution were added. In addition, the chamber was outfitted with crew quarters, hygiene areas, storage, and workspaces. Teams across the Johnson Space Center (JSC) worked together to overcome the logistical and operational challenges of the planned test parameters. The ultimate goal was to create an analog testbed in which a maximum of eight human test subjects could safely live and work for at least 11 days in the same conditions (e.g., reduced pressures, oxygen concentrations, and so on) as those expected inside a base spacecraft. This would allow researchers to study the effects of such environments on humans and to validate proposed Prebreathe Protocols to enable the safe performance of surface extravehicular activities (EVAs). Over the last 18 months, the CTSD Systems Test Branch has performed six tests of varying lengths and atmospheres for both NASA and commercial partners. To date, researchers now have collected data on 48 test subjects in the course of 42 days and over 130 simulated EVAs. This paper will discuss the history of the 20 Foot Chamber, its long road to becoming an analog testbed for human exploration, and the capabilities that make it a unique, world class facility for NASA and commercial human exploration missions. It will provide an overview of past and future testing and the lessons learned along the way.

Cristina A Anchondo↗
NASA NTRSDate not supplied

Creating the Test Environment for Exploration Habitats

The Crew and Thermal Systems Division’s (CTSD) 20 Foot Chamber has undergone significant modifications to support NASA’s future human exploration missions to the Moon, Mars, and beyond. Existing chamber systems such as Vacuum/Repress, Heating Ventilation and Air Conditioning (HVAC), and Fire Suppression System (FSS), were upgraded, while new systems such as Air Revitalization and Gas Distribution were added. In addition, the chamber was outfitted with crew quarters, hygiene areas, storage, and workspaces. Teams across the Johnson Space Center (JSC) worked together to overcome the logistical and operational challenges of the planned test parameters. The ultimate goal was to create an analog testbed in which a maximum of eight human test subjects could safely live and work for at least 11 days in the same conditions (e.g., reduced pressures, oxygen concentrations, and so on) as those expected inside a base spacecraft. This would allow researchers to study the effects of such environments on humans and to validate proposed Prebreathe Protocols to enable the safe performance of surface extravehicular activities (EVAs). Over the last 18 months, the CTSD Systems Test Branch has performed six tests of varying lengths and atmospheres for both NASA and commercial partners. To date, researchers now have collected data on 48 test subjects in the course of 42 days and over 130 simulated EVAs. This paper will discuss the history of the 20 Foot Chamber, its long road to becoming an analog testbed for human exploration, and the capabilities that make it a unique, world class facility for NASA and commercial human exploration missions. It will provide an overview of past and future testing and the lessons learned along the way.

Chris Briggs↗
DOE OSTI2025

Coupled Induction Machine and HVAC Models for Simulating HVAC Performance Considering Grid Dynamics in Buildings

This paper presents the development of novel models that integrate induction machines with HVAC equipment, such as pumps, heat pumps, and chillers, to analyze the impact of electrical parameters on the operational performance of thermo-fluid systems. The proposed model employs a coupling technique that captures the dynamic interactions between induction machines and HVAC systems. By integrating electrical, thermal, and mechanical dynamics, the models provide a comprehensive framework for simulating real-world scenarios, including interactions with the electrical grid. This achievement was made possible through the development of a Computationally Efficient and Accurate Induction Machine (CEAIM) model. Implemented using the equation-based Modelica language, the CEAIM model has been validated against experimental results, manufacturer data sheets, and various operating conditions. Its performance has been compared with existing induction machine models in the Modelica Standard Library (MSL), demonstrating superior accuracy and computational efficiency. The CEAIM model predicts torque, speed, and power consumption with a coefficient of determination (R 2 ) ranging from 0.98 to 1 and a coefficient of variation of root mean square error (CVRMSE) between 0.27% and 6.67%. Additionally, CEAIM scales more efficiently than conventional MSL models, with a slower computational growth rate in large-scale simulations. After thorough validation of the CEAIM model, it was coupled with HVAC equipment as this approach provides a detailed multi-dimensional view of capturing electrical transients and mechanical performance. To support this, a case study was conducted to showcase its capabilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Development of a simplified calibrated building simulation model of a supermarket for proposed ECMs and control strategies impact evaluation

Calibrated building energy simulation is an important pathway to more energy-efficient buildings, but the information requirements of some approaches to this problem are significant. This is particularly true for supermarkets and other so-called “big-box” retail stores. Another characteristic of supermarkets is the significant interaction between Heating Ventilating and Air Conditioning (HVAC) and refrigeration systems in these buildings. These buildings could contain a wide variety of systems and a degree of load diversity that makes calibrated modeling a challenge. This paper describes a simplified approach that uses OpenStudio and EnergyPlus to combine known building parameters with “typical” parameters, resulting in a simplified building that is amenable to calibration. This approach was applied to a big-box store located in Nashville, Tennessee, and a calibrated model was obtained that was used to study potential energy conservation measures. Further, the paper also explores the capabilities of whole-building energy modeling tools, such as EnergyPlus, for modeling the HVAC controls and sequences and their impact evaluation. Although some measures are precluded by the model simplicity, several measures were found to improve the efficiency of the model and demonstrate that the simplified modeling approach is effective. Practical Application: This paper introduces a hybrid approach of building energy model calibration using limited information available from the actual building in combination with characteristics of a “typical” building of the same type. This hybrid approach would also be applicable for other building types than discussed in this paper to calibrate the building energy model using limited information from the actual building.

42 ENGINEERING↗
DOE OSTI2024

Frozen Freedom: Unleashing Grocery Store Demand Flexibility: Preprint

Grocery stores consumed approximately 3% of total electricity used by commercial buildings in the U.S. in 2018 (EIA 2018), representing a unique end-use load profile characterized by the critical use of refrigerated display cases. Exploring demand response (DR) scenarios in grocery stores presents an opportunity to enhance the efficiency and sustainability of surrounding communities. In addition, recent studies demonstrate that implementing control algorithms considering demand flexibility strategies can lead to load and peak reductions in standalone refrigerated display cases. Because small business grocery stores operate on thin margins, the energy bill cost savings DR might provide could make a positive difference toward continued operations. Still, uncertainty remains about the extent of demand flexibility potential controls could provide when coupling refrigeration with whole building operation. To enhance economic viability and grid stability, it is essential to quantify the load flexibility capability of grocery stores. Advanced controls can optimize energy consumption by responding to load shedding, shifting, and DR events, as well as daily Time-of-Use (TOU) rates without compromising food safety. Using both quantitative data and interviews with community-based organizations, we developed a full-size store model and two small store models with controlled refrigerated cases, HVAC, and lighting systems based on actual grocery store properties. Through simulations, we have assessed load flexibility strategies with varied DR events. The results highlight potential for energy and peak reduction with advanced or basic controls. However, interviews and data indicate that more support is needed to make DR strategies consistently accessible to small grocery stores.

demand flexibility↗
DOE OSTI2022

Towards a Stronger Foundation: Digitizing Commercial Buildings with Brick to Enable Portable Advanced Applications

Most large commercial buildings have digital controls for their heating, ventilation, and air-conditioning (HVAC) and lighting systems with the potential to implement advanced control strategies and data analytics. However, advanced control strategies and data analytics are rarely deployed at scale due to non-standard naming conventions and heterogenous building configurations. Semantic metadata standards, like Brick, show promise to proliferate these applications across many buildings, but they have not been widely adopted by industry due to barriers such as perceived risk and unfamiliarity with the technology. This paper describes the workflow we established and evaluated while using it to develop over ten Brick models of existing buildings. Through this process, we observed that digitizing existing commercial buildings is a cost and labor-intensive effort in which understanding the buildings’ data streams is the major bottleneck. Yet, we conclude this investment is worthwhile since various use case applications such as fault detection and diagnostics, thermal comfort analysis, and HVAC control optimization can utilize the same Brick model. The paper also explores the challenges and lessons learned we encountered while creating these data models, such as: 1) difficulties in finding metadata descriptions and relationships for existing buildings; 2) handling missing concepts in the schema needed to model a building; 3) lack of guidance on how to structure the data model or how much detail to include; 4) unfamiliarity with technologies, which makes the learning curve steep for applications developers. Finally, we also describe future directions for semantic metadata research and development to make such transformative technologies more accessible to practitioners.

Roa, Carlos Duarte↗
DOE OSTI2025

The health and indoor environmental quality impacts of residential building envelope retrofits: A literature review

Retrofitting existing buildings to improve energy efficiency is an important strategy to meet increasingly stringent energy efficiency targets. While the primary objective of energy efficiency retrofits is to reduce energy consumption and greenhouse gas emissions, retrofits can also result in non-energy impacts (NEIs), which contribute to decision-making processes and overall value of the retrofit. NEIs have been studied extensively in retrofitted residential buildings; however, these studies have historically grouped passive (i.e., building envelope) and active (i.e., heating, ventilation, and air conditioning (HVAC) and energy system) upgrades, making it difficult to identify the underlying mechanism(s) of action for each NEI and developing effective retrofit strategies, based on occupant need. The purpose of this study was to better account for NEIs, based on a literature review, summarizing the current state of knowledge on NEIs associated with residential building envelope retrofits. We limited our search to health- and indoor environmental quality-related NEIs. The review identified strong evidence that building envelope retrofits improve acoustic comfort, wintertime thermal comfort, and respiratory and cardiovascular health outcomes. IAQ outcomes were mixed, with studies reporting both increases and decreases to indoor contaminant concentrations following retrofits. The strength of the effect was generally governed by pre-retrofit contaminant concentrations and whether indoor concentrations were dominated by indoor or outdoor sources. Most studies evaluating summertime thermal comfort identified increased incidence of summertime overheating; however, none of these studies linked the change in thermal conditions to health outcomes. Recommendations for future work include expanding studies to include more market rate housing and the health impacts of summertime overheating in retrofitted buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

State-of-the-art on research and applications of machine learning in the building life cycle

Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Finally, findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

EnergyPlus-MCP: A model-context-protocol server for ai-driven building energy modeling

Traditional building energy modeling with the EnergyPlus building performance simulation engine requires domain expertise, programming skills, and intensive manual efforts limiting its effective adoption. This paper introduces EnergyPlus-MCP, the first open-source Model Context Protocol (MCP) server specifically designed for EnergyPlus simulation workflows, establishing a new foundational infrastructure for AI-driven building energy modeling. The MCP server implements a layered architecture with 35 specialized tools spanning model management, editing and analysis, HVAC and other systems configuration inspection, and simulation execution, enabling Large Language Models to interact with EnergyPlus through conversational interfaces. The server addresses critical workflow barriers by automating model validation, streamlining energy efficiency measures modification, and providing intelligent output management with interactive visualization. Through practical demonstrations using a multi-zone building retrofit analysis, we show how the EnergyPlus-MCP server significantly reduces manual efforts while maintaining full simulation rigor. By providing accessible natural language interfaces to sophisticated building energy analysis, this approach enables scalable deployment of simulation expertise across public and private organizations, educational institutions, and research teams, fundamentally transforming traditional building energy modeling practices.

AI↗
DOE OSTI2020

Development and Evaluation of Occupancy-Aware Model Predictive Control for Residential Building Energy Efficiency and Occupant Comfort

The residential sector accounts for 25% of global primary energy consumption. Two methods have previously been proposed to reduce residential energy use associated with the provision of occupant thermal comfort: 1. Occupancy-based HVAC control, operating systems only during confirmed occupancy, and 2. model predictive control (MPC), harnessing a mathematical model and forecasts to find optimal operating strategies. Previous studies estimate the average energy savings of the two methods individually in the range of 21% and 16%, respectively. The research presented herein was carried out to evaluate the energy savings potential in residential buildings by combining both approaches across different climates, house vintages, and occupancy patterns. Occupancy and eight different physical modalities (e.g. CO2 and VOC) data were collected from five homes for time periods of 4–9 weeks. Collected data sets were used to train occupancy prediction models suggested by an extensive literature survey of occupancy model types. The trained prediction models were combined with MPC and detailed EnergyPlus building simulation models to evaluate residential building performance in terms of annual energy savings and thermal comfort, along with discomfort exceedance metrics. Multiple home types and regions were analyzed to understand regional and climate-dependent potential. Based on actual field data, the occupancy models had a prediction inaccuracy between 8% and 35% across the investigated homes. Average occupancy for the collected data ranged from 56% to 86%, a typical range reported in the literature. Building simulations were conducted for three control scenarios: conventional thermostatic control, occupancy-based, and occupancy-based MPC. The results indicate that all advanced strategies improve upon the conventional control, with some scenarios cutting energy use in half with only occasional incurrence of discomfort. The findings indicate that occupancy-aware model predictive residential building control has the potential to drastically reduce energy use and associated emissions while maintaining occupant comfort for both new and existing buildings.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗