SEARCH · Engineering Papers

Results for “building”

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 865 records · Page 48

All sources NASA NTRS DOE OSTI

DOE OSTI2024

The Best of Both Worlds: Combined Thermal and Battery Storage for Widespread Building Decarbonization

To meet 2050 decarbonization targets, widespread building electrification is a critical complement to clean power generation. Behind-the-meter storage (BTMS) (e.g., battery electric energy storage [EES] and thermal energy storage [TES]) integrated with buildings or building end uses to store and supply energy at optimal times can minimize burdens associated with operation, planning, and upgrades to the electrical grid sometimes triggered by building electrification. Such BTMS systems can serve the dual purpose of providing enhanced resilience at the building and grid level, and support the deployment of renewable generation needed for wide-scale decarbonization. While TES can cost-effectively shed and shift thermal loads, it cannot generally backup or shift non-thermal building end uses. EES, by contrast, is more expensive, but applicable to all end uses (i.e., thermal and electrical loads). Combined together, these storage systems can be traded off against one another to perform optimally in meeting demand flexibility, decarbonization goals, and energy resilience of the buildings at a lower total system cost. This paper proposes a framework to define BTMS benefits, provides four illustrative electrification scenarios using TES and EES, and discusses the combined TES/EES benefits with building energy modeling results. The paper also highlights potential barriers to adoption of BTMS and a path forward.

buildings↗

DOE OSTI2026

Ten questions concerning Large Language Models (LLMs) for building applications

Large Language Models (LLMs) are emerging as powerful AI tools capable of transforming how building information is collected, processed, analyzed, and applied across diverse research areas. Their capabilities can help building operators, facility managers and other stakeholders such as designers, architects and engineers by providing actionable insights for decision-making across planning, construction, operations, and maintenance of buildings and facilities. This paper explores ten key questions concerning the role of LLMs in shaping sustainable, intelligent, and human-centric buildings. From fundamental definitions to advanced applications, we examine how LLMs facilitate decision-making across the life cycle of buildings and energy systems. LLMs can enhance life cycle assessments (LCA), building energy simulations, and real-time data integration, empowering more efficient and adaptive human-AI environments. They can also contribute to streamlining regulatory compliance, improving post-occupancy evaluations, and fostering more inclusive and participatory design processes. Additionally, this paper addresses the ethical challenges posed by LLMs, such as bias, data privacy, and environmental impacts, and explores their potentials in advancing intelligent digital twins (DT) for ongoing building operations and maintenance. Built upon our applied research using LLMs and the review of tools, datasets, and research gaps, we provide a forward-looking perspective on how LLMs can drive innovation, collaboration, and productivity in the built environment while supporting ethical and effective implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Active learning strategy for high fidelity short-term data-driven building energy forecasting

The quality of a data-driven model is heavily dependent on the quality of data. Data from building operation often have data bias problems, which means that the data sample is collected in a way that some members of the intended data population are less likely to be included than others. Data-driven energy forecasting models built on such data hence are biased and could lead to large forecasting errors. Active learning—an effective method to defying data bias—is rarely studied or applied in the area of data-driven building energy forecasting modeling. This paper attempts to fill this gap and explores the application of active learning in data-driven building energy forecasting. The developed strategy in this paper efficiently generate informative training data within a time budget and uses block design to passively consider weather disturbances. The developed active learning strategy is applied and evaluated in both virtual and real-building testbeds against traditional data-driven methods. Via these virtual and real-building evaluation cases, we have demonstrated that the data bias problem typically exists in building operation data is resolved by applying the developed active learning strategy. Furthermore, building energy forecasting models trained from data generated from the active learning strategy have shown improved performances in both model accuracy and model extendibility perspectives. The effectiveness of the block design module is also validated to effectively consider the impact of weather conditions on active learning design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

A comparative analysis of green building rating systems in China and the United States

Several studies have compared green building rating systems (GBRSs) in China and the United States, Nonetheless, few studies included in-depth analysis on specific rating tools with project specific data validating green building technologies and actual performance. This study conducted a comprehensive data-driven comparison of the GBRSs of China and the United States. The goal was to understand the current status and further improve China's GBRS and promote green building technologies. The study first conducted thorough comparisons of GBRSs in China and the U.S. by selecting a series of distinct rating tools. Then, it analyzed each tool's development objectives, contents, and rating score settings. Further, the comparison concludes the future development needs for China's GBRS. In addition to standard comparison, green building technologies applied in certified projects were also summarized. The results demonstrated that GBRSs in both China and the U.S. reflect well the technical paths to achieve green building sustainable development. By analyzing certified projects, it was also found that the incremental costs of green building technologies were controllable. Finally, based on the comparison and case analysis, the study provide a set of policy recommendations to further improve China's green building standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2011

Renewable Energy Requirements for Future Building Codes: Options for Compliance

As the model energy codes are improved to reach efficiency levels 50 percent greater than current codes, use of on-site renewable energy generation is likely to become a code requirement. This requirement will be needed because traditional mechanisms for code improvement, including envelope, mechanical and lighting, have been pressed to the end of reasonable limits. Research has been conducted to determine the mechanism for implementing this requirement (Kaufman 2011). Kaufmann et al. determined that the most appropriate way to structure an on-site renewable requirement for commercial buildings is to define the requirement in terms of an installed power density per unit of roof area. This provides a mechanism that is suitable for the installation of photovoltaic (PV) systems on future buildings to offset electricity and reduce the total building energy load. Kaufmann et al. suggested that an appropriate maximum for the requirement in the commercial sector would be 4 W/ft 2 of roof area or 0.5 W/ft 2 of conditioned floor area. As with all code requirements, there must be an alternative compliance path for buildings that may not reasonably meet the renewables requirement. This might include conditions like shading (which makes rooftop PV arrays less effective), unusual architecture, undesirable roof pitch, unsuitable building orientation, or other issues. In the short term, alternative compliance paths including high performance mechanical equipment, dramatic envelope changes, or controls changes may be feasible. These options may be less expensive than many renewable systems, which will require careful balance of energy measures when setting the code requirement levels. As the stringency of the code continues to increase however, efficiency trade-offs will be maximized, requiring alternative compliance options to be focused solely on renewable electricity trade-offs or equivalent programs. One alternate compliance path includes purchase of Renewable Energy Credits (RECs). Each REC represents a specified amount of renewable electricity production and provides an offset of environmental externalities associated with non-renewable electricity production. The purpose of this paper is to explore the possible issues with RECs and comparable alternative compliance options. Existing codes have been examined to determine energy equivalence between the energy generation requirement and the RECs alternative over the life of the building. The price equivalence of the requirement and the alternative are determined to consider the economic drivers for a market decision. This research includes case studies that review how the few existing codes have incorporated RECs and some of the issues inherent with REC markets. Section 1 of the report reviews compliance options including RECs, green energy purchase programs, shared solar agreements and leases, and other options. Section 2 provides detailed case studies on codes that include RECs and community based alternative compliance methods. The methods the existing code requirements structure alternative compliance options like RECs are the focus of the case studies. Section 3 explores the possible structure of the renewable energy generation requirement in the context of energy and price equivalence. The price of RECs have shown high variation by market and over time which makes it critical to for code language to be updated frequently for a renewable energy generation requirement or the requirement will not remain price-equivalent over time. Section 4 of the report provides a maximum case estimate for impact to the PV market and the REC market based on the Kaufmann et al. proposed requirement levels. If all new buildings in the commercial sector complied with the requirement to install rooftop PV arrays, nearly 4,700 MW of solar would be installed in 2012, a major increase from EIA estimates of 640 MW of solar generation capacity installed in 2009. The residential sector could contribute roughly an additional 2,300 MW based on the same code requirement levels of 4 W/ft 2 of roof area. Section 5 of the report provides a basic framework for draft code language recommendations based on the analysis of the alternative compliance levels.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2013

Recovery Act: Advanced Interaction, Computation, and Visualization Tools for Sustainable Building Design

Current building energy simulation technology requires excessive labor, time and expertise to create building energy models, excessive computational time for accurate simulations and difficulties with the interpretation of the results. These deficiencies can be ameliorated using modern graphical user interfaces and algorithms which take advantage of modern computer architectures and display capabilities. To prove this hypothesis, we developed an experimental test bed for building energy simulation. This novel test bed environment offers an easy-to-use interactive graphical interface, provides access to innovative simulation modules that run at accelerated computational speeds, and presents new graphics visualization methods to interpret simulation results. Our system offers the promise of dramatic ease of use in comparison with currently available building energy simulation tools. Its modular structure makes it suitable for early stage building design, as a research platform for the investigation of new simulation methods, and as a tool for teaching concepts of sustainable design. Improvements in the accuracy and execution speed of many of the simulation modules are based on the modification of advanced computer graphics rendering algorithms. Significant performance improvements are demonstrated in several computationally expensive energy simulation modules. The incorporation of these modern graphical techniques should advance the state of the art in the domain of whole building energy analysis and building performance simulation, particularly at the conceptual design stage when decisions have the greatest impact. More importantly, these better simulation tools will enable the transition from prescriptive to performative energy codes, resulting in better, more efficient designs for our future built environment.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2014

Balancing Hydronic Systems in Multifamily Buildings

In multifamily hydronic systems, temperature imbalance may be caused by undersized piping, improperly adjusted balancing valves, inefficient water temperature and flow levels, and owner/occupant interaction with the boilers, distribution and controls. The effects of imbalance include tenant discomfort, higher energy use intensity and inefficient building operation. This paper explores cost-effective distribution upgrades and balancing measures in multifamily hydronic systems, providing a resource to contractors, auditors, and building owners on best practices to improve tenant comfort and lower operating costs. The research was conducted by The Partnership for Advanced Residential Retrofit (PARR) in conjunction with Elevate Energy. The team surveyed existing knowledge on cost-effective retrofits for optimizing distribution in typical multifamily hydronic systems, with the aim of identifying common situations and solutions, and then conducted case studies on two Chicago area buildings with known balancing issues in order to quantify the extent of temperature imbalance. At one of these buildings a booster pump was installed on a loop to an underheated wing of the building. This study found that unit temperature in a multifamily hydronic building can vary as much as 61 degrees F, particularly if windows are opened or tenants use intermittent supplemental heating sources like oven ranges. Average temperature spread at the building as a result of this retrofit decreased from 22.1 degrees F to 15.5 degrees F.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

VOLTTRON™: Tech-to-Market Best-Practices Guide for Small- and Medium-Sized Commercial Buildings

VOLTTRON™ is an open-source distributed control and sensing platform developed by Pacific Northwest National Laboratory for the U.S. Department of Energy. It was developed to be used by the Office of Energy Efficiency and Renewable Energy to support transactive controls research and deployment activities. VOLTTRON is designed to be an overarching integration platform that could be used to bring together vendors, users, and developers and enable rapid application development and testing. The platform is designed to support modern control strategies, including the use of agent- and transaction-based controls. It also is designed to support the management of a wide range of applications, including heating, ventilation, and air-conditioning systems; electric vehicles; and distributed-energy and whole-building loads. This report was completed as part of the Building Technologies Office’s Technology-to-Market Initiative for VOLTTRON’s Market Validation and Business Case Development efforts. The report provides technology-to-market guidance and best practices related to VOLTTRON platform deployments and commercialization activities for use by entities serving small- and medium-sized commercial buildings. The report characterizes the platform ecosystem within the small- and medium-sized commercial building market and articulates the value proposition of VOLTTRON for three core participants in this ecosystem: 1) platform owners/adopters, 2) app developers, and 3) end-users. The report also identifies key market drivers and opportunities for open platform deployments in the small- and medium-sized commercial building market. Possible pathways to the market are described—laboratory testing to market adoption to commercialization. We also identify and address various technical and market barriers that could hinder deployment of VOLTTRON. Finally, we provide “best practice” tech-to-market guidance for building energy-related deployment efforts serving small- and medium-sized commercial buildings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

When Walls Talk, Buildings Can Be Made Better

What if your building could “tell” you how to save money? PNNL is inventing systems to turn buildings from passive users of energy into active participants in the power system—making the buildings we work or live in “work” for us instead. We’re researching how buildings can respond intelligently to the natural environment, evolving grid conditions and dynamic occupant demands—not simply bracing for those external factors. Why do buildings matter to our energy future? Senior Engineer Nora Wang says it’s because buildings account for 75 percent of U.S. electricity consumption and 40 percent of our nation’s energy use overall. That equates to $430 billion in energy bills every year. Powering U.S. buildings contributes more than 2,200 million metric tons of carbon dioxide to the atmosphere annually—more than the total emissions of Russia and Canada combined.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

A Methodology for Defining Affordability in Commercial Buildings and its Impact on Underserved Communities

Commercial buildings are at the heart of any community. Investments towards the health and performance of community buildings can support a wide range of critical community and individual benefits; however, many buildings have been left behind in these investments due to a spectrum of barriers, especially those located in underserved communities. This portfolio of work stands with the intent that if we can create solutions to support the hardest-to-reach commercial buildings in gaining equitable access to energy efficiency, zero energy, and zero carbon solutions, we can support all commercial buildings with these goals. To understand success and barriers, and identify new, innovative, and impactful solutions, NREL is taking a four-part approach to: 1. Develop a methodology for defining affordability in commercial buildings and understand its impact on underserved communities, 2. Work with trusted, local organizations to address barriers that impede access to cost-effective, holistic, building performance improvements, 3. Support minority-focused developer incubator programs for, and within, underserved communities, and 4. Identify overlapping value streams that support underserved community and utility needs.

building electrification↗

DOE OSTI2014

Calibrating Building Energy Models Using Supercomputer Trained Machine Learning Agents

Building Energy Modeling (BEM) is an approach to model the energy usage in buildings for design and retrofit purposes. EnergyPlus is the flagship Department of Energy software that performs BEM for different types of buildings. The input to EnergyPlus can often extend in the order of a few thousand parameters which have to be calibrated manually by an expert for realistic energy modeling. This makes it challenging and expensive thereby making building energy modeling unfeasible for smaller projects. In this paper, we describe the Autotune research which employs machine learning algorithms to generate agents for the different kinds of standard reference buildings in the U.S. building stock. The parametric space and the variety of building locations and types make this a challenging computational problem necessitating the use of supercomputers. Millions of EnergyPlus simulations are run on supercomputers which are subsequently used to train machine learning algorithms to generate agents. These agents, once created, can then run in a fraction of the time thereby allowing cost-effective calibration of building models.

Sanyal, Jibonananda↗

DOE OSTI2016

Comparative study of the cooling energy performance of variable refrigerant flow systems and variable air volume systems in office buildings

Variable air volume (VAV) and variable refrigerant flow (VRF) systems are widely used in office buildings. This study investigated VAV and VRF systems in five typical office buildings in China, and compared their cooling energy use. Site survey and field measurements were conducted to collect the data of building characteristics and operation. Measured cooling electricity use was collected from sub-metering in the five buildings. The sub-metering data normalized by climate and operating hours indicated that the cooling energy consumed by VRF systems was up to 70% lower than that consumed by VAV systems. This was mainly because of the different operation modes of both system types that led to significantly fewer operating hours for the VRF systems. Building simulations were used to quantify the impact of operation modes of VRF and VAV systems on cooling loads. A prototype office building in China was used as the model. The simulation results showed that the VRF operation mode required much lower cooling load when compared to the VAV operation mode. For example, the cooling loads decreased by 42% in Hong Kong and 53% in Qingdao. Key findings include the following: the VRF systems operated in the part-time-part-space mode enabling occupants to turn on the air-conditioning only when needed and when the spaces were occupied. However, the VAV systems operated in the full-time-full-space mode limiting occupants’ control of operation. These findings provide insights into VRF systems operation and controls as well as their energy performance, which could help guide HVAC designers on system selection and building operators or facility managers on system operations to achieve low- or zero-net energy buildings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

A review of select human-building interfaces and their relationship to human behavior, energy use and occupant comfort

In recent years, research has emerged to quantitatively and qualitatively understand occupants' interactions with buildings. However, there has been surprisingly little research on building interfaces and how their design, context (e.g., location), and underlying logic impact their usability and occupants’ perceived control, as well as the resulting comfort and energy performance. This means that research is needed to better understand how occupants interact with building interfaces in both commercial and residential applications; both applications are important to address as there are many differences in interface types, level of control and understanding, and even expectations of engagement. Herein, this paper provides a cursory review and discussion of select common building interfaces: windows, window shades/blinds, thermostats, and lighting controls. The goal of this paper is to review literature related to these human-building interfaces to explore interface characteristics, current design and use challenges, and relationships between building interfaces and occupants. Human-building interface interactions are complex, more research is needed to understand design, use, and characteristics. Common themes emerged throughout the literature review to explain occupant interactions (or lack of interactions) with building interfaces, which included thermal and visual comfort, ease and access of control, interface/control placement, poor interface/control design, lack of understanding, and social-behavioral dynamics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Urban-scale building energy consumption database: a case study for Wuhan, China

Building energy consumption accounts for 30% of the overall energy end use worldwide. This number is even much higher in urban areas. With rapid urbanization in China, cities are expanding with new constructions. It is essential to create an updated urban-scale building energy consumption database to represent energy use for different types of buildings in China, which could help urban planners, managers and decision makers to understand temporal and spatial building energy consumption distribution and ensure required electricity and/or gas supply. However, such urban-scale database is rarely found in China. This paper creates baseline EnergyPlus models for residential, small office and large office buildings and validates the baseline models using survey data from literature. Parametric simulations are conducted to consider different design factors, such as building enclosure, lighting power density, equipment power density, HVAC schedule, etc. In total 351 EnergyPlus models are generated to cover different energy use intensity scenarios. Data-driven regression analysis is conducted to predict building energy consumption using building price/rent. The prediction results are expected to provide design decision support for urban planning and power distribution for new constructions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Real time side-by-side experimental validation of energy and comfort performance of a zero net energy retrofit package for small commercial buildings

Making buildings zero-net energy (ZNE) is one of the major strategies for achieving carbon emission reduction goals. For this strategy to be successful, it entails a very significant reduction in energy use – 50% or more. In small commercial buildings, however, owners and building management teams usually have limited resources for identifying, analyzing, and procuring appropriate retrofit measures for reducing such use. An approach to overcome this limitation is the development of bundles of energy efficiency measures that can be presented to building owners/operators as a comprehensive package. The research presented in this paper focuses on an experimental evaluation of the impacts of a retrofit package developed for small office buildings in California. Performing this evaluation in a full-scale whole-building integrated systems test facility allowed a side-by-side evaluation in real time, against a reference case, of the impact of the retrofit package not only on energy use but also on visual and thermal comfort. Here, the retrofit package evaluated is comprised of a combination of HVAC, lighting (including daylighting), and plug load measures. The evaluation occurred at different times of the year in order to account for seasonal variations in environmental conditions, including solar angles and weather. The experimental facility allowed testing for two different façade orientations: south and west. Results show that the proposed ZNE retrofit package can save significant amounts of energy for small commercial buildings. During cooling-prevalent periods, total energy savings were 65% for south orientation and 68% for west orientation; during heating-prevalent periods total energy savings were 22% for south orientation and 25% for west orientation. Measurements indicate that the ZNE retrofit package resulted in small but not very significant changes in comfort levels for building occupants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

A product data network to enable faster, easier, and better planning of building envelopes

The building envelopes contributes significantly to the energy-efficiency of the building. Building performance simulation has made it possible to compare façade technologies regarding energy demand, daylighting, thermal and visual comfort in detail. Planners, such as architects and engineers, need experience to find product data with the right quality and level of detail, and to process the data to fit the calculation and the application. In the available time, planners can compare only a limited number of products, which means that better solutions could go unnoticed. This paper presents a new concept for making product data easily accessible for building façade planning. The concept consists of a network of databases for the efficient exchange and use of optical and calorimetric data of glazing units, shading devices, and combinations of both. The paper presents the research questions, an analysis of the current challenges, six design goals for the product data network and its implementation together with a discussion. Many product data sources can be connected to many planning software applications via the specified application programming interface. When planning software connects to the product data network, the planning of building envelopes can be much faster because planners do not need to spend so much time to search and process product data manually. The planning of building envelopes can also become much easier, especially for planners with limited experience. They do not need to understand all the details about which data fits which calculation if the software company implements this. The planning of building envelopes can become much more reliable when software companies validate their use of the product data network, because the current manual process is prone to errors. The planning of building envelopes can also improve because more products can be compared in the available time, allowing better solutions to be found.

Maurer, Christoph↗

DOE OSTI2025

A machine learning method of modern urban building energy modeling: A case study of Chicago

Urban-scale building energy modeling is vital for urban planning. However, it can be challenging to assimilate reliable non-geometry building data for urban-scale modeling without extensive investment. Here, this study introduces a novel approach to developing modern urban-scale building energy stock data using geographic information systems and machine learning algorithms without necessarily requiring pre-supplied non-geometric metadata. The proposed framework integrates building footprint and height data to estimate gross floor areas, and matches each building to a pool of candidate records from ComStock or ResStock—filtered to the same county and ranked by geometric similarity—demonstrate a proof-of-concept case study in Chicago for predicting energy use intensity (EUI) using scalable datasets. The model achieved a mean bias error (MBE) of 0.08 kWh/m² and root mean square error (RMSE) of 14.84 kWh/m² under full metadata input for EUI prediction. With only location inputs, the model captured 69.2 % of EUI within predicted ranges. These results demonstrate the model’s potential to support early-stage urban planning, identify candidates for energy-efficient retrofits. By removing the dependency on detailed pre-surveys or extensive building metadata, the approach overcomes a key barrier in traditional urban-scale building energy modeling, illustrating a pathway toward broader and more cost-effective application, though further multi-city validation and improved treatment of pre-1925 buildings are needed.

Energy Use Intensity↗

DOE OSTI2022

Datasets of a Multizone Office Building under Different HVAC System Operation Scenarios

Abstract This study provides an open-source dataset of the measured weather data, building indoor data, and system data under the different test settings. The test building is the two-story Flexible Research Platform building at the US Department of Energy’s Oak Ridge National Laboratory, in Oak Ridge, Tennessee. Four heating tests and three cooling tests were conducted. The 1-min interval of weather, building indoor data, and system data from each test setting are provided. Actual weather data were collected from a weather station installed on the roof. This paper describes information on the test building and installed sensors, data collection method, and data validation. The provided dataset can be employed to understand HVAC system conditions and building indoor conditions under different HVAC system operations and the performance of building envelope without HVAC system operation using free-floating test data. Additionally, it can be used for empirical validation of the building energy modelling engine.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗