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DOE OSTI2021

DOE Deep Energy Retrofit Cost Survey

A survey was conducted by the Lawrence Berkeley National Laboratory on deep energy retrofit (DER) market drivers, opportunities, and challenges. The survey was part a research study sponsored by the U.S. Department of Energy to gather information on the costs of DER from home performance contractors and stakeholders. Cost data was gathered from DER projects that use a comprehensive, whole-home approach to drastically reduce energy use and improve performance. DER projects often aim at reducing energy use by 50% or more. In addition, these projects can improve home comfort and potentially benefiting occupant health. Yet, market adoption of DER has been limited. Major limiting factors include complex projects, high costs, perceived risks, extensive disruption, and unfamiliar work scopes to some contractors. In order to better understand what motivates and deters DER projects in today’s market, a survey was conducted to gather this information, and to learn about promising approaches and technologies from the industry perspective. Past surveys on homeowners and home energy performance professionals have studied the motivations and barriers of energy efficiency retrofits. Two surveys of home energy performance professionals were conducted in recent years. The Resources for the Future (RFF) Home Energy Audit and Retrofit Survey was conducted in 2011 by recruiting energy auditors and retrofit installers through members of Efficiency First and Building Performance Institute (BPI) accredited contractors. The survey asked about the business and services that respondents provide, how often homeowners follow their recommendations to retrofit their homes, and the respondents’ opinion on barriers faced by the industry. The survey found that not enough homeowners know about energy audits, but more importantly, it is the high cost of retrofits compared to low energy prices that is responsible for few energy audits and retrofits being completed. The RESNET Deep Retrofit Industry Stakeholder Survey was conducted shortly after launching of the EnergySmart Home Performance Team program. The EnergySmart Team program involves a formal agreement among allied contractors who are engaged in high performance retrofits. Using this allied team approach, teams can pool their expertise and provide each other with customer referrals. The survey asked EnergySmart Team members and outside stakeholders on questions about market and technical barriers in performing home energy retrofits. Survey respondents identified lack of consumer awareness and lack of affordable financing for consumers as the leading market barriers to home energy retrofits. In their written comments, many survey respondents also echoed that the high costs of retrofit compared to low energy prices is a market barrier. Respondents found “certain housing characteristics that prevent effective retrofit” and “energy analysis software inaccuracy or limitations” are the two leading technical barriers. Their choices for technical barriers were reflective of the energy rater/auditor role played by the majority (78%) of the survey respondents. In comparison to past surveys, this work aimed to gather inputs from a broader segment of the home performance industry to identify the opportunities and barriers faced by DERs from all perspectives. The survey asks for project costs to help breakdown the high costs of DERs. This survey is also motivated by a need to better understand the role of DERs in reducing energy use by the residential sectors and meeting climate goals. The survey is designed towards obtaining more substantive inputs from survey respondents by encouraging written comments, rather than setting the goal to reach a large number of respondents. We took this approach because DER is currently still a niche market, so it is more valuable to gather in-depth inputs from individuals who are performing this work rather than getting to the masses.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Smart Labs Final Report Summer 2021

The Smart Labs Project at Los Alamos National Laboratory (LANL) is an initiative derived from The University of California, Irvine and is part of the Department of Energy’s (DOE) Better Buildings Challenge. These carbon abatement strategies aim to reduce energy consumption of laboratories while also maintaining health and safety requirements. Smart Labs designs incorporate seven key principles which are: digital control systems, demand-based ventilation, low power-density demand-based lighting, exhaust fan discharge velocity optimization, pressure drop optimization, fume hood flow optimization, and commissioning with automated cross-platform fault detection. As the ALDCP Smart Labs team for the summer of 2021, the scope of the project is to determine the energy savings within building 03-1698 (Material Science Laboratory - MSL). Over the past couple of years, the Sustainability Group has been adding Smart Labs upgrades into the MSL building and the summer team would like to understand the impact made for the overall energy consumption/demand and safety for the building, determine the overall return on investment (ROI), and recommend more Smart Labs upgrades that can be added to the MSL building. The goal is to enable the UI FOD (Utilities and Infrastructure Facility Operation Division) to promote more Smart Labs projects in the future and further the reputation LANL and DOE facilities have of being leading examples of developers of high performing buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1994

Shared Problem Models and Crew Decision Making

The importance of crew decision making to aviation safety has been well established through NTSB accident analyses: Crew judgment and decision making have been cited as causes or contributing factors in over half of all accidents in commercial air transport, general aviation, and military aviation. Yet the bulk of research on decision making has not proven helpful in improving the quality of decisions in the cockpit. One reason is that traditional analytic decision models are inappropriate to the dynamic complex nature of cockpit decision making and do not accurately describe what expert human decision makers do when they make decisions. A new model of dynamic naturalistic decision making is offered that may prove more useful for training or aiding cockpit decision making. Based on analyses of crew performance in full-mission simulation and National Transportation Safety Board accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation and reflect the crew's metacognitive skill. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relation between communication that serves to build performance. Implications of these findings for crew training will be discussed.

Orasanu, Judith↗

DOE OSTI2015

Simulation and Field Evaluation Support for ESTCP Dynamic Windows: Cooperative Research and Development Final Report, CRADA Number CRD-12-492

We will leverage new building performance and daylighting simulation tools to characterize the performance of a new electrochromic (EC) glazing as well as perform a field evaluation of the same product installed in a DoD facility. The in situ data will be used to validate and calibrate the simulation model, which will then be used to extrapolate the performance of the product across all US climate zones. The property as part of this agreement will be installed at MCAS Miramar, California.

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 OSTI2017

Smart ventilation energy and indoor air quality performance in residential buildings: A review

To better address energy and indoor air quality issues, ventilation needs to become smarter. A key smart ventilation concept is to use controls to ventilate more at times it provides either an energy or indoor air quality (IAQ) advantage (or both) and less when it provides a disadvantage. A favorable context exists in many countries to include some of the existing smart ventilation strategies in codes and standards. As a result, demand-controlled ventilation (DCV) systems are widely and easily available on the market, with more than 20 DCV systems approved and available in countries such as Belgium, France and the Netherlands. This paper provides a literature review on smart ventilation used in residential buildings, based on energy and indoor air quality performance. This meta-analysis includes 38 studies of various smart ventilation systems with control based on CO 2 , humidity, combined CO 2 and total volatile organic compounds (TVOC), occupancy, or outdoor temperature. In conclusion, these studies show that ventilation energy savings up to 60% can be obtained without compromising IAQ, even sometimes improving it. However, the meta-analysis included some less than favorable results, with 26% energy overconsumption in some cases.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

A new database of building-space-specific internal loads and load schedules for performance based code compliance modeling of commercial buildings

Building-level loads and load profiles prescribed by current modeling rules save modelers time and avoid gaming during whole building performance modeling. However, recent studies show that they sometimes insufficiently capture the entire building performance due to the varied loads and load profiles for different space types. As a solution to this issue, this paper develops a database of building-space-specific loads and load profiles used in code compliance modeling. The existing sets of loads and load profiles are reviewed and the challenges behind using them for specific research topics are discussed. Then, the proposed method to develop the building-space-specific loads and load profiles is introduced. After that, the database for these building-space-specific loads and load profiles is presented. In addition, one case is studied to demonstrate the applications of these loads and load profiles. In this case study, three methods are used to develop building energy models: space-specific (using knowledge of the distribution and location of space types and applying the space-specific data in the developed database), building-level (assuming a lack of knowledge of the space types and using the building-level data in the developed database), and calculated-ratio (assuming knowledge of the distribution of space types but not their locations and calculating weighted average values based on the space-specific data in the developed database). Finally, the energy results simulated by using these three methods are compared, which show building-level methods can produce energy results up to 20% different than the space-specific methods. Finally, this paper discusses the application scope and maintenance of this new database.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Equation-based object-oriented modeling and simulation for data center cooling: A case study

© 2019 Elsevier B.V. Data center cooling accounts for about 1% of electricity usage in the United States. Computer models are pivotal in designing and operating energy-efficient cooling systems. Compared to conventional building performance simulation programs, the equation-based object-oriented modeling language Modelica is an emerging approach that can enable fast prototyping and dynamic simulation of cooling systems. In this case study, we first modeled the cooling and control systems of an actual data center located in Massachusetts using the open-source Modelica Buildings library, and then calibrated a baseline model based on measurement data. The simulation of the baseline model identified several operation-related issues in the cooling and control systems, such as degraded cooling coils, improper dead band in control settings, and simultaneous cooling and heating in air handlers. Afterwards, we used a sequential search technique as well as an optimization scheme to investigate the energy saving potentials for different energy efficiency measures aiming to address the abovementioned issues. Simulation results show potential energy savings up to 24% by resolving identified control-related issues and optimizing the supply air temperature.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Characterization of a contaminated facility and associated soils in support of D and D and subsequent soil remediation - 15292

Before starting any D and D field work at a United States Department of Energy (DOE) facility such as the Savannah River Site (SRS), it is recommended that a complete review and understanding of the full nature and extent of any contamination located in or previously associated with that facility is known. An integral aspect of this review and research entails a complete characterization of that facility, including, but not limited to, Toxic Substances Control Act (TSCA) limits for Polychlorinated Biphenyl (PCB), radiological, Resource Conservation and Recovery Act of 1976 (RCRA) and other hazardous chemicals, etc. A thorough characterization of a facility and its underlying soils supports: - establishment of safe working conditions to protect human health and environment - Deactivation and Decommissioning (D and D) methodology - cost estimates to support future budget planning for D and D and soil cleanup A prime example of this is documented in the characterization of the 690-N, Process Heat Exchanger Repair Facility that had a history of PCB and radioactive contamination. Characterization of 690-N included the sampling and analysis of concrete and underlying soils for radiological, PCB and hazardous contaminants. In addition, a sump, the walls of the facility, expansion joint material and the metal base of a drill press were characterized. Results of this comprehensive characterization of the 690-N Building are provided in a detailed report. Analytical results indicate minimal radiological, PCB, or RCRA hazardous contamination is present in the concrete floor slab (industrial exposure levels) and on the steel hut walls. Soils below the concrete floor slab show only trace amounts of radiological contamination and are well below TSCA and RCRA limits. Subsequent decommissioning/demolition activities can be performed safely without harming people or the environment, and cost estimates to perform building demolition can be developed for future budget planning. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1979

Energy efficient engine: High pressure turbine uncooled rig technology report

Results obtained from testing five performance builds (three vane cascades and two rotating rigs of the Energy Efficient Engine uncooled rig have established the uncooled aerodynamic efficiency of the high-pressure turbine at 91.1 percent. This efficiency level was attained by increasing the rim speed and annulus area (AN(2)), and by increasing the turbine reaction level. The increase in AN(2) resulted in a performance improvement of 1.15 percent. At the design point pressure ratio, the increased reaction level rig demonstrated an efficiency of 91.1 percent. The results of this program have verified the aerodynamic design assumptions established for the Energy Efficient Engine high-pressure turbine component.

Gardner, W. B.↗

DOE OSTI2014

DOE Zero Energy Ready Home Case Study: One Sky Homes — Cottle Zero Net Energy Home, San Jose, CA

This builder took home the Grand Winner prize in the Custom Builder category in the 2014 Housing Innovation Awards for its high performance building science approach. The builder used insulated concrete form blocks to create the insulated crawlspace foundation for its first DOE Zero Energy Ready Home, the first net zero energy new home certified in the state of California.

2014 housing innovation awards↗

DOE OSTI2014

Technology Solutions Case Study: Combustion Safety for Appliances Using Indoor Air

This case study describes how to assess and carry out the combustion safety procedures for appliances and heating equipment that uses indoor air for combustion in low-rise residential buildings. Only appliances installed in the living space, or in an area freely communicating with the living space, vented alone or in tandem with another appliance are considered here. This document is for inspectors, auditors, and technicians working in homes where energy upgrades are being conducted whether or not air infiltration control is included in the package of measures being applied. In the indoor combustion air case, guidelines summarized here are based on language provided in several of the codes to establish minimum requirements for the space using simplified prescriptive measures. In addition, building performance testing procedures are provided by testing agencies. The codes in combination with the test procedures offer comprehensive combustion safety coverage to address safety concerns, allowing inexperienced residential energy retrofit inspectors to effectively address combustion safety issues and allow energy retrofits to proceed.

Building America↗

DOE OSTI2021

Utilizing ensemble learning for performance and power modeling and improvement of parallel cancer deep learning CANDLE benchmarks

Abstract Machine learning (ML) continues to grow in importance across nearly all domains in modeling to learn from data. Often a tradeoff exists between a model's ability to minimize bias and variance. In this article, we utilize ensemble learning to combine linear, nonlinear, and tree‐/rule‐based ML methods to cope with the bias‐variance tradeoff and result in more accurate models. We use the datasets collected for two parallel cancer deep learning CANDLE benchmarks, NT3 and P1B2, to build performance and power models based on hardware performance counters using single‐object and multiple‐objects ensemble learning to identify the most important counters for improvement on the Cray XC40 Theta at Argonne National Laboratory. Based on the insights from these models, we improve the performance and energy of P1B2 and NT3 by optimizing the deep learning environments TensorFlow, Keras, Horovod, and Python under the huge page size of 8 MB. Experimental results show that ensemble learning not only produces more accurate models but also provides more robust performance counter ranking. We achieve up to 61.15% performance improvement and up to 62.58% energy saving for P1B2 and up to 55.81% performance improvement and up to 52.60% energy saving for NT3 on up to 24,576 cores.

Wu, Xingfu↗

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↗

DOE OSTI2014

Combustion Safety for Appliances Using Indoor Air (Fact Sheet)

This measure guideline covers how to assess and carry out the combustion safety procedures for appliances and heating equipment that uses indoor air for combustion in low-rise residential buildings. Only appliances installed in the living space, or in an area freely communicating with the living space, vented alone or in tandem with another appliance are considered here. A separate measure guideline addresses combustion appliances located either within the living space in enclosed closets or side rooms or outside the living space in an adjacent area like an attic or garage that use outdoor air for combustion. This document is for inspectors, auditors, and technicians working in homes where energy upgrades are being conducted whether or not air infiltration control is included in the package of measures being applied. In the indoor combustion air case, guidelines summarized here are based on language provided in several of the codes to establish minimum requirements for the space using simplified prescriptive measures. In addition, building performance testing procedures are provided by testing agencies. The codes in combination with the test procedures offer comprehensive combustion safety coverage to address safety concerns, allowing inexperienced residential energy retrofit inspectors to effectively address combustion safety issues and allow energy retrofits to proceed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Measure Guideline: Combustion Safety for Natural Draft Appliances Using Indoor Air

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Measure Guideline: Combustion Safety for Natural Draft Appliances Using Indoor Air

This Measure Guideline covers how to assess and carry out the combustion safety procedures for appliances and heating equipment that uses indoor air for combustion in low-rise residential buildings. Only appliances installed in the living space, or in an area freely communicating with the living space, vented alone or in tandem with another appliance are considered here. A separate Measure Guideline addresses combustion appliances located either within the living space in enclosed closets or side rooms or outside the living space in an adjacent area like an attic or garage that use outdoor air for combustion. This document is for inspectors, auditors, and technicians working in homes where energy upgrades are being conducted whether or not air infiltration control is included in the package of measures being applied. In the indoor combustion air case, guidelines summarized here are based on language provided in several of the codes to establish minimum requirements for the space using simplified prescriptive measures. In addition, building performance testing procedures are provided by testing agencies. The codes in combination with the test procedures offer comprehensive combustion safety coverage to address safety concerns, allowing inexperienced residential energy retrofit inspectors to effectively address combustion safety issues and allow energy retrofits to proceed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

Thermographic Microstructure Monitoring in Electron Beam Additive Manufacturing

To reduce the uncertainty of build performance in metal additive manufacturing, robust process monitoring systems that can detect imperfections and improve repeatability are desired. One of the most promising methods for in-situ monitoring is thermographic imaging. However, there is a challenge in using this technology due to the difference in surface emittance between the metal powder and solidified part being observed that affects the accuracy of the temperature data collected. This developed a method for properly calibrating temperature profiles from thermographic data and then determining important characteristics of the build through additional processing. The thermographic data was analyzed to determine the transition of material from metal powder to a solid as-printed part. A corrected temperature profile was then assembled for each point using calibrations for these surface conditions. Using this data, we calculated the thermal gradient and solid-liquid interface velocity and correlated it to microstructural variation within the part experimentally. This work shows that by using a method of process monitoring, repeatability of a build could be monitored specifically in relation to microstructure control.

36 MATERIALS SCIENCE↗