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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Radiometric Testing of Germicidal UV Products, Round 1: UV-C Towers and Whole-Room Luminaires (CALiPER Full Report)

This report analyzes the independently tested performance of 13 germicidal ultraviolet (GUV) products purchased between February and July 2022. The products were of three different types: • Seven portable, consumer-oriented GUV towers designed to be placed on the floor or a desk of an unoccupied room to disinfect air and surfaces. Five of these products used LED sources and two products had low-pressure mercury (LPM) sources. • One GUV whole-room luminaire designed to be installed on a ceiling to disinfect air when a room is occupied. This product had LED sources. • Five GUV troffer or high-bay style whole-room luminaires designed to be installed in or suspended from a ceiling to disinfect air and surfaces when a room is unoccupied. All five had LPM sources. Product testing covered radiometric and electrical performance for all 13 products as well as photobiological safety evaluation if product documentation included testable claims. Measurement results enable comparison between products and against manufacturer or vendor claims. Testing identified numerous issues related to the accuracy of claimed GUV product performance. Claims were often untestable, contradictory, ambiguous, or used incorrect units and/or terminology. When claims were testable, they often did not match test results. For example, three LED products that claimed to emit UV-C emitted only UV-A. Product claim issues were more common among consumer-oriented tower products, but all product types exhibited problems with accurate performance claims. The UV-C radiant efficiency (calculated as UV-C output power divided by electrical input power) of the products varied widely, even among similar products using the same source technologies. For example, the UV-C radiant efficiency of LPM products varied by greater than a factor of three for the same product type, indicating a large potential energy savings opportunity for products that are better designed for efficiency. LED products had orders-of-magnitude lower UV-C radiant efficiency than LPM products. This study also identified several testing challenges and limitations. Most significant among these is the capability to accurately test and report the performance of larger GUV products. Whereas integrating spheres are used to quickly measure total radiant flux (i.e., output power) and spectral distribution, goniometers are used to measure radiant intensity distribution (from which radiant flux can be calculated). Integrating spheres require a specialized and costly coating to test UV, and the testing laboratory for this round of products had only a 20-inch diameter hemisphere with this capability. The integrating sphere accommodated just 2 of the 10 UV-C emitting products. Goniometer testing had a different size limitation in that mirrors typically used to increase goniometer test distance to the far field reflect little to no UV. As a result, the study evaluated only 6 of 13 products in the far field. Electronic files of UV-C intensity data for the other 7 products, which would typically be imported into design software for designing GUV applications, may not be reliable for predicting irradiance at arbitrary far-field distances (IES 2022a; CIE 2020). Specifiers and buyers of GUV products need accurate performance claims and data to deploy GUV technology safely and effectively. This CALiPER GUV Round 1 report demonstrates the significant education and training manufacturers and vendors still require to accurately test and report the performance of their GUV products. Further industry standards and guidelines may address testing limitations and improve test methods, product performance, and the accuracy of performance claims.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Microscopic Evidence for Scission Neutrons

We discuss the neck rupture stage of fission and the emission of particles afterwards, two extremely rapid and highly non-equilibrium processes. Currently, the neck rupture cannot be directly probed by experiment, highlighting the importance of reliable theoretical predictions for this stage of fission. Time-dependent density functional theory (TDDFT) is used to simulate the spontaneous fission of 252 Cf. In conjunction with statistical models, inputs from microscopic calculations can be used to make predictions for prompt neutron and gamma emission spectra, quantities which can be experimentally measured. Here we characterize the scission mechanism within TDDFT and estimate the number of scission neutrons and their kinetic energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

RAFT: Reconfigurable Array of High-Efficiency Ducted Turbines for Hydrokinetic Energy Harvesting

Diversifying the energy harvesting portfolio is crucial to achieving the ambitious goal of transitioning to clean energy by 2030. Marine hydrokinetic energy has garnered renewed interest due to its high harvesting potential in the U.S., and the resource's reliability and predictability—remaining relatively constant on a daily basis and available 24/7. However, there are currently few commercial devices capable of harnessing the energy from flowing water. This project aims to bridge that gap by designing and evaluating a novel hydrokinetic turbine concept that can efficiently harvest energy from both rivers and tidal streams. The RAFT (Reconfigurable Array of High-Efficiency Ducted Turbines) concept introduces a duct surrounding the turbine rotor and creates an array of small 5-kW units. The duct serves two primary purposes: (1) it enhances hydrodynamic efficiency by accelerating flow to the rotor, and (2) it functions as a structural component, facilitating the formation of modular arrays that lower costs. This project focuses on demonstrating this concept and validating these benefits through simulations and scaled prototype testing. The project team includes 8 faculty members and over 20 students from 3 universities, organized into three core areas: hydrodynamics, electrical systems, and structural analysis, with additional teams dedicated to system integration, environmental assessment and risk management, and tech-to-market strategy. The team successfully demonstrated the increased hydrodynamic efficiency of a ducted turbine compared to an unducted version using high-fidelity simulations and prototype tests. Moreover, design optimization efforts led to surpassing the SHARKS program's goal of 60% reduction of the levelized cost of energy with a significant margin.

13 HYDRO ENERGY↗
DOE OSTI2023

Radiometric Testing of Germicidal UV Products, Round 1: UV-C Towers and Whole-Room Luminaires (CALiPER Full Report)

This report analyzes the independently tested performance of 13 germicidal ultraviolet (GUV) products purchased between February and July 2022. The products were of three different types: • Seven portable, consumer-oriented GUV towers designed to be placed on the floor or a desk of an unoccupied room to disinfect air and surfaces. Five of these products used LED sources and two products used low-pressure mercury (LPM) sources. • One non-portable GUV whole-room luminaire designed to be installed on a ceiling to disinfect air when a room is occupied. This product used an LED source. • Five non-portable GUV troffer or high-bay style whole-room luminaires designed to be installed in or suspended from a ceiling to disinfect air and surfaces when a room is unoccupied. All five used LPM sources. Radiometric and electrical performance was evaluated for all 13 products. Photobiological safety was also assessed for two of the products because their documentation included testable claims. The test results were compared across products and to manufacturer or vendor claims. The testing identified many issues related to the accuracy of reported GUV product performance. Claims were often untestable, contradictory, ambiguous, or used incorrect units and/or terminology. And when claims were testable, they often did not match test results. For example, three products that claimed to emit UV-C emitted only UV-A. These product claim issues were more numerous with consumer-oriented tower products, but problems with accurate performance claims were found across all products. The UV-C radiant efficiency of the products varied widely, even among similar products using the same source technologies. For example, the UV-C radiant efficiency of LPM products varied by greater than a factor of three for the same product type, indicating a large potential energy savings opportunity for products that are better designed for efficiency. LED products had orders-of-magnitude lower UV-C radiant efficiency than LPM products. Several testing challenges and limitations were identified. Most significant among these is the capability to accurately test and report the performance of larger GUV products. Integrating spheres require a specialized and costly coating to test UV, and the testing laboratory for this round of products had only a 20-inch diameter hemisphere with this capability. Only 2 of the 10 UV-C emitting products could be tested in this sphere. Goniometer testing had a different size limitation in that mirrors typically used to increase goniometer test distance to the far field are not reflective of UV and therefore could not be used to increase test distance. As a result, 7 of 13 products could not be tested far field. The implication is that electronic files of UV-C intensity data typically imported into design software for designing GUV applications may not be reliable for predicting irradiance at arbitrary far-field distances. It is currently unclear if these are industry-wide testing laboratory limitations, and what solutions may exist to address them. Specifiers and buyers of GUV products will need accurate performance claims and data to safely and effectively deploy GUV technology to reduce the transmission of diseases in buildings. This CALiPER GUV Round 1 report demonstrates the significant education and training that is needed for manufacturers and vendors to accurately test and report the performance of their GUV products. Further standards and guidelines are needed to improve test methods, address testing limitations, and improve reporting of product performance. Additionally, the wide range in UV-C radiant efficiency of GUV products means there is a large energy-savings opportunity for more energy efficient GUV products.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Radiometric Testing of Germicidal UV Products, Round 1: UV-C Towers and Whole-Room Luminaires (CALiPER Summary Report)

This summary report analyzes the independently tested performance of 13 germicidal ultraviolet (GUV) products purchased between February and July 2022. A companion full report provides additional information and discussion of the tested products, test methods, and results. The products were of three different types: • Seven portable, consumer-oriented GUV towers designed to be placed on the floor or a desk of an unoccupied room to disinfect air and surfaces. Five of these products used LED sources and two products used low-pressure mercury (LPM) sources. • One non-portable GUV whole-room luminaire designed to be installed on a ceiling to disinfect air when a room is occupied. This product used an LED source. • Five non-portable GUV troffer or high-bay style whole-room luminaires designed to be installed in or suspended from a ceiling to disinfect air and surfaces when a room is unoccupied. All five used LPM sources. Radiometric and electrical performance was evaluated for all 13 products. Photobiological safety was also assessed for two of the products because their documentation included testable claims. The test results were compared across products and to manufacturer or vendor claims. The testing identified many issues related to the accuracy of reported GUV product performance. Claims were often untestable, contradictory, ambiguous, or used incorrect units and/or terminology. And when claims were testable, they often did not match test results. For example, three products that claimed to emit UV-C emitted only UV-A. These product claim issues were more numerous with consumer-oriented tower products, but problems with accurate performance claims were found across all products. The UV-C radiant efficiency of the products varied widely, even among similar products using the same source technologies. For example, the UV-C radiant efficiency of LPM products varied by greater than a factor of three for the same product type, indicating a large potential energy savings opportunity for products that are better designed for efficiency. LED products had orders-of-magnitude lower UV-C radiant efficiency than LPM products. Several testing challenges and limitations were identified. Most significant among these is the capability to accurately test and report the performance of larger GUV products. Integrating spheres require a specialized and costly coating to test UV, and the testing laboratory for this round of products had only a 20-inch diameter hemisphere with this capability. Only 2 of the 10 UV-C emitting products could be tested in this sphere. Goniometer testing had a different size limitation in that mirrors typically used to increase goniometer test distance to the far field are not reflective of UV and therefore could not be used to increase test distance. As a result, 7 of 13 products could not be tested far field. The implication is that electronic files of UV-C intensity data typically imported into design software for designing GUV applications may not be reliable for predicting irradiance at arbitrary far-field distances. It is currently unclear if these are industry-wide testing laboratory limitations, and what solutions may exist to address them. Specifiers and buyers of GUV products will need accurate performance claims and data to safely and effectively deploy GUV technology to reduce the transmission of diseases in buildings. This CALiPER GUV Round 1 report demonstrates the significant education and training that is needed for manufacturers and vendors to accurately test and report the performance of their GUV products. Further standards and guidelines are needed to improve test methods, address testing limitations, and improve reporting of product performance. Additionally, the wide range in UV-C radiant efficiency of GUV products means there is a large energy-savings opportunity for more energy efficient GUV products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Electrode Erosion and Prefire Studies Towards Fusion Scale Pulsed Power

This study presents a comprehensive investigation of electrode erosion and discharge behavior in spark gap switches over long switching cycle lifetimes. Brass, copper–tungsten (CuW), and stainless steel electrodes are tested under controlled conditions to quantify material degradation, debris accumulation, and changes in breakdown voltage. High-resolution imaging and statistical analysis of spark channel locations and gap breakdown voltages reveal how surface evolution influences long-term performance and reliability. These results provide essential data for lifetime modeling and inform design strategies for pulsed power systems in emerging applications such as private sector fusion energy and large-scale facilities like Sandia’s Z Machine and proposed ZX upgrades, where high repetition reliability and predictable behavior are critical.

electrical breakdown↗
DOE OSTI2026

Added value of site load measurements in probabilistic lifetime extension: a Lillgrund case study

Site-specific fatigue estimation is an essential part of wind turbine lifetime extension, with various methods depending on data availability. The present study compares probabilistic lifetime extension assessment results for rotor blades with and without load measurements. It also addresses two key questions in such assessments: the applicability of the Frandsen model for estimating waked turbulence under complex and mixed wake conditions and the extrapolation of mid-term data over longer time periods. The case study wind turbine is SWT-2.3-93, located at the edge of the Lillgrund wind farm, situated in the Øresund Strait between Denmark and Sweden. The turbine is extensively instrumented, with 5 years of data available from its supervisory control and data acquisition (SCADA) system. Although the Frandsen turbulence estimates deviate in a different manner from measurements at below- and above-rated mean wind speeds, the model remains a conservative approach for fatigue load prediction and reliability. In the current case study, the site-specific assessment using strain gauge measurements yields a 33 % higher annual fatigue reliability index after 35 years compared to a scenario based on the Frandsen estimation combined with ambient environmental data and a generic aeroelastic model. The results also demonstrate that the sensitivity of fatigue reliability to load uncertainty is negligible when load measurements are used directly but relatively high when relying on the Frandsen model in combination with a generic aeroelastic model. Overall, the high variability of the lifetime extension in different scenarios of data availability and accuracy shows the importance and added value of high-quality measurements combined with wind-farm-level SCADA and a model updated in real time (digital twins).

17 WIND ENERGY↗
DOE OSTI2021

FCIC Task 5--Preprocessing

the objective of this project is to develop science-based design and operation principles (as informed by TEA and LCA), which result in preprocessing units to operate predictably and reliably, and are capable of scalable performance.

09 BIOMASS FUELS↗
DOE OSTI2022

Wind Energy Accomplishments & Midyear Performance Report: Fiscal Year 2022

2022 marks 43 years of innovation through the National Wind Technology Center at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) Flatirons Campus. Scientists, engineers, analysts, and researchers continue to build on NREL's legacy of innovation at this world-class hub for wind energy technology research and development. Today, the nation's goals to tackle climate change and revitalize the U.S. economy through increased investment in clean energy - particularly in land-based, offshore, and distributed wind energy - are more ambitious than ever. From advancing wind energy science, technologies, and materials to demonstrating thought leadership on a worldwide scale, NREL's Wind Energy Program played a powerful role in maximizing the impact of wind energy in the first half of Fiscal Year (FY) 2022. NREL's technical expertise, research capabilities, and industry understanding continued to support DOE's efforts to champion clean energy, addressing market and deployment barriers and driving down costs with more efficient, reliable, and predictable wind energy systems. This report provides an overview of the achievements NREL made on behalf of DOE's Wind Energy Technologies Office (WETO) and other partners between October 1, 2021, and March 31, 2022.

accomplishments↗
DOE OSTI2023

Wind Energy Accomplishments and Year-End Performance Report: Fiscal Year 2022

Four decades ago, construction was just beginning on experimental turbines at the National Wind Technology Center (NWTC). Today, the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) facility is the centerpiece of the laboratory's Flatirons Campus, a world-class hub for renewable energy research. The nation's shift to 100% clean electricity by 2035 will require a mix of renewable energy sources and strategies - and together, wind and solar energy could account for 60% to 80% of that clean energy resource. In Fiscal Year (FY) 2022, NREL scientists, engineers, and analysts contributed to these visionary goals through their wind energy research. As wind innovations push into new areas, NREL continues to play a vital role in advancing technology and addressing deployment barriers in pursuit of more efficient, reliable, and predictable wind energy systems. FY 2022 wind research and development explored the potential for dramatic growth in land-based systems, the launch of the nation's first commercial-scale offshore installations, and transmission infrastructure buildout. Land-based wind energy is one of the most cost-effective electricity supply options - but utility-scale deployment will require up to 10 times the current number of turbines. An NREL plan addressed this need to accelerate U.S. wind technology rollout at distributed and utility scales. Another project conducted by NREL and the Pacific Northwest National Laboratory (PNNL) helps position the nation's first major offshore wind corridor for success. The WETO-funded Atlantic Offshore Wind Transmission Study is evaluating options for balancing electricity supply and demand, while supporting resilience of the grid and marine industries. WETO, NREL, and other partners are working to enable the enormous supply chain and workforce changes the U.S. wind energy industry will need to meet net-zero-carbon-emissions targets. As part of a seminal series of DOE-funded supply chain studies, NREL analysts reported on the trade-offs involved in manufacturing large volumes of wind technologies, while addressing cost, workforce, and logistics issues. All of this research is supported by NREL's outstanding research teams, tools, data, and facilities. A WETO-funded international wind energy field campaign, the American WAKE experimeNt (AWAKEN), has brought together experts from NREL, PNNL, and Sandia National Laboratories to create the world's most comprehensive set of high-resolution data on wind energy atmospheric phenomenon. This study could lead to more accurate predictions of losses from turbine-to-turbine wake interactions, eventually helping wind plants capture more energy and operators save millions of dollars. In addition, NREL researchers developed testing, modeling, and analysis tools to improve the security of power grids by identifying wind power plant dynamic stability problems. A new Stochastic Soaring Raptor Simulator (SSRS) protects golden eagles from turbine encounters by predicting flight paths. This report provides more detail on these top achievements and other accomplishments made by NREL and its partners during FY 2022 (between October 1, 2021, and September 30, 2022).

accomplishments↗
DOE OSTI2023

Dynamic Model Agnostic Reliability Evaluation of Machine-Learning Models Integrated in Instrumentation & Control Systems

In recent years, the field of machine learning (ML), specifically neural networks, has grown significantly and has spurred research in its applicability to digital instrumentation and control systems (DI&C). While ML models have shown promise in operational contexts, the trustworthiness of using such algorithms has not been adequately assessed. Failures of ML integrated systems are not well understood, and the lack of comprehensive risk modeling can degrade the trustworthiness in these systems. In recent reports by the National Institute for Standards and Technology (NIST) [1] and the Nuclear Regulatory Commission (NRC) [2], they indicate that trustworthiness in ML is a critical barrier and will play a vital role in the safe, accountable, and secure operation of intelligent systems. Thus, in this work, we demonstrate a dynamic model-agnostic method to quantify the relative reliability of AI/ML predictions by incorporating out-of-distribution (OOD) detection on the training dataset. It is well documented that most ML algorithms excel at interpolation (or near-interpolation) tasks but experience significant performance degradation at extrapolation. The method, referenced as the Laplacian distributed decay for reliability (LADDR), determines the difference between the operational and training datasets which can used to the relative reliability of AI/ML predictions. LADDR is then demonstrated on a feedforward neural network based digital twin used for the prediction of safety significant factors during a loss-of-flow transient. LADDR is used to demonstrate how training data can be used as evidence to support the relative reliability of ML/AI predictions enhancing the overall trustworthiness of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Dynamic Model Agnostic Reliability Evaluation of Machine-Learning Models Integrated in Instrumentation & Control Systems

In recent years, the field of data-driven neural network-based machine learning (ML) algorithms has grown significantly and spurred research in its applicability to instrumentation and control systems. While they are promising in operational contexts, the trustworthiness of such algorithms is not adequately assessed. Failures of ML-integrated systems are poorly understood; the lack of comprehensive risk modeling can degrade the trustworthiness of these systems. In recent reports by the National Institute for Standards and Technology, trustworthiness in ML is a critical barrier to adoption and will play a vital role in intelligent systems' safe and accountable operation. Thus, in this work, we demonstrate a real-time model-agnostic method to evaluate the relative reliability of ML predictions by incorporating out-of-distribution detection on the training dataset. It is well documented that ML algorithms excel at interpolation (or near-interpolation) tasks but significantly degrade at extrapolation. This occurs when new samples are "far" from training samples. The method, referred to as the Laplacian distributed decay for reliability (LADDR), determines the difference between the operational and training datasets, which is used to calculate a prediction's relative reliability. LADDR is demonstrated on a feedforward neural network-based model used to predict safety significant factors during different loss-of-flow transients. LADDR is intended as a "data supervisor" and determines the appropriateness of well-trained ML models in the context of operational conditions. Ultimately, LADDR illustrates how training data can be used as evidence to support the trustworthiness of ML predictions when utilized for conventional interpolation tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The Reliability of Hybrid Functionals for Accurate Fundamental and Optical Gap Prediction of Bulk Solids and Surfaces

Hybrid functionals have been considered insufficiently reliable for the prediction of band gaps in solids and surfaces. We revisit this issue with a new generation of optimally tuned range-separated hybrid functionals, focusing on the reconstructed Si(111)-(2×1) and Ge(111)-(2×1) surfaces. We show that certain hybrid functionals can accurately predict the surface-state and bulk fundamental and optical gaps, as well as projected band structures of these surfaces, by combining ground-state and time-dependent density functional theory.

Sagredo, Francisca↗
DOE OSTI2024

Enabling Efficient Surveillance, Control, and Automation of Geothermal Operations with Advanced Predictive Analytics

Automation and control of geothermal energy production and operations require reliable and efficient predictive tools. While physics-based simulation offers a comprehensive tool for predicting energy production performance in geothermal systems, predicting the behavior of geothermal reservoirs involves complex multi-physics processes with coupling effects, highly uncertain input parameters and subsurface descriptions. Moreover, building, running, and integrating simulation models into standard model calibration and optimization workflows entail significant technical and computational efforts. An emerging alternative to physics-based simulation is data-driven predictive analytics models that have gained popularity in energy industry. In this report, we develop novel predictive models for integration into real-time fault diagnosis and model predictive control algorithms to improve the efficiency of energy production operations in geothermal reservoirs. The report includes two major research Thrust Areas, that is, the surface power plant and the subsurface reservoir.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

A Multiphysics Multiscale Simulation Platform for Damage, Environmental Degradation, and Life Prediction of CMCs in Extreme Environments

This project successfully developed a multiphysics, multiscale computational framework to enhance the design and development of CMCs, with a focus on modeling highly nonlinear, time-dependent damage mechanisms and material degradation under extreme conditions, such as those experienced in turbine service environments. The project made significant advances in improving our understanding of progressive damage, oxidative degradation, and time-dependent inelastic deformation in CMCs, with particular attention to the role of uncertainties in predictions. Key outcomes include the integration of advanced material characterization, uncertainty quantification, and multiphysics constitutive models to predict the behavior of CMCs over their service life. A novel multiscale methodology was employed, which integrated microscale constituent behaviors with structural-scale responses, enabling the manufacturing defects in the microstructure that are prone to damage nucleation. Through the development of DL algorithms, the project advanced the prediction of damage initiation and crack propagation, taking into account the defect morphology and statistical variations across multiple scales. The framework was rigorously validated using thermomechanical experiments, which tested CMCs under various mechanical loadings at elevated temperatures, further enhancing the model's predictive capability. Overall, the research outcomes have provided a more accurate, reliable method for predicting CMC component life, significantly advancing material design, and improving component reliability in extreme environments. This work has strong implications for the optimization of turbine components and other high-performance applications where CMCs are used.

03 NATURAL GAS↗
DOE OSTI2021

Wind Turbine Drivetrain Reliability Assessment and Remaining Useful Life Prediction

This presentation describes a methodology for predicting probability of failure of wind turbine gearbox bearings failed by axial cracking. This methodology was applied to a commercial MW size wind plant and generated results were correlated with actual failures. This work is partnered with WindESCo and funded through DOE's Technology Commercialization Fund.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2019

Probabilistic reliability assessment and case studies for predicted energy savings in residential buildings

This study aims to (1) investigate the key influential parameters (KIPs) in estimating the uncertainty of energy savings using a residential building energy simulation model and (2) perform uncertainty quantification for energy savings for several different scenarios. The proposed methodology was successfully applied to the calculation of uncertainties associated with residential energy retrofits using two test houses designed for pre- and post-retrofit cases. Uncertainties were determined using basic parameters that might be supplied to an energy model and then reevaluated based on an audit of the KIPs identified, resulting in substantially reduced uncertainty. Of four different scenarios, the most uncertain scenario estimated the annual energy savings from the retrofit would be between 18% and 51% at a 95% confidence level, and the least uncertain scenario estimated the annual savings would be between 26% and 40% at a 95% confidence level. The actual measured annual savings from the two test houses was 28%, which shows an agreement with the uncertainty analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗