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At least 559 records · Page 31

Extract useful information from building permits data to profile a city’s building retrofit history

Building retrofit is one of the key strategies for cities to reduce energy use and GHG emissions. The historical information about changes to buildings is crucial to infer the buildings’ current energy system efficiency levels and to identify candidate buildings for retrofit. In general, a building permit is required before the start of any construction activity of a building, such as changing building structure, remodeling, or installing new equipment. Moreover, many large cities provide public datasets of building permits in history. Therefore, the permits are a potentially good resource for mining information on the city’s retrofit history. In this study, we use the permit dataset from the city of San Francisco as a case study. Location and time information from the dataset is also used to depict the retrofit timeline of each building and the whole building stock. The type of work of the permit is inferred from the descriptive text by a machine learning model. At last, the limitations of the current permit dataset and potential improvements on the permit data management are discussed to better utilize the information in the future.

Zhang, Wanni↗

A New Campus Built on Efficiency

The University of California (UC), Merced partnered with the U.S. Department of Energy (DOE) to develop and implement solutions to reduce energy consumption by as part of DOE’s Commercial Buildings Partnerships (CBP) Program. Lawrence Berkeley National Laboratory (LBNL) provided technical expertise in support of this DOE program. This case study reports on the process and outcome of this project including the achieved savings from design improvements for the campus. The intent of the project was to retrofit the Science & Engineering (S&E) building and the central plant at UC Merced to achieve up to 30% energy reduction. The anticipated savings from these retrofits represented about 17% of whole-campus energy use. If achieved, the savings contribution from the CBP project would have brought overall campus performance to 56% of the 1999 UC/CSU benchmark performance for their portfolio of buildings. However, the final design that moved forward as part of the CBP program only included the retrofit measures for the S&E building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Systems Engineering Tutorial with Case Studies

Due to the ever-growing number of complex technical problems facing our world, a Systems Engineering approach is needed to assist in successful design, build and implementation of solutions. The interdisciplinary technical structure of current systems, technical processes representing System Design, Technical Management and Product Realization are instrumental in the development and integration of new technologies into mainstream applications. This tutorial will demonstrate the application of Systems Engineering tools to these types of problems. Learning objectives include, understanding how to develop and engineer a conceptual system; understand the importance of teams, communication, requirements definition, interface control, and focus on deliverables; useful tools and techniques for each aspect of the System Engineering process including Model Based Systems Engineering which will be touched upon lightly. Some hands-on problems will be pursued especially in requirements development which is always key to a successful project. Case studies will be presented to assist in the learning process.

Systems Engineering↗

Guest Room Lighting at the Hilton Columbus Downtown

At the Hilton Columbus Downtown hotel in Ohio, DOE's Better Buildings Alliance conducted a demonstration of Next Generation Luminaires-winning downlights installed in all guest rooms and suites prior to the hotel's 2012 opening. After a post-occupancy assessment, the LED downlights not only provided the aesthetic appearance and dimming functionality desired, but also provided 50% energy savings relative to a comparable CFL downlight and enabled the lighting power to be more than 20% below that allowed by code. This document is a summary case study of the report.

gateway, ssl, doe, solid-state, better buildings, ↗

Long term performance of vacuum insulation panels integrated into building components

Vacuum insulation panels provide much greater resistance to heat transfer than conventional insulation materials, making them ideal for building applications, especially where space is a constraint. Of particular interest is energy retrofits where high insulation values are required with very little or no modifications to existing building envelope elements such as fenestrations and service penetrations. To facilitate the use of vacuum insulation panels (VIPs) in residential and commercial construction, this study investigates the performance of VIPs integrated into polyisocyanurate foam board and vinyl siding after several years of service. Vacuum insulation panels integrated with polyisocyanurate boards were studied in mixed humid and cold climates. The integration of VIPs with vinyl siding was investigated in a mixed humid climate. Periods of service were between two and five years. In all cases, the integrated building components outperformed conventional materials by almost 40 percent during heating and cooling periods. However, the percent reduction in heat gains and losses of the integrated building components decreased with time at a rate between approximately 4% and 10% per year during the service period. In some cases, the rate seems to converge to a steady -state value. Measurements are ongoing to determine if a steady-state value is attained or the panel's insulation value continues to decrease with time. This study is critical in addressing the service life and durability of the building envelope with VIP integrated building components. The effect of these changes will be reviewed in the context of an exterior retrofit.

Aldykiewicz Jr, Antonio↗

Mapping Inundation from Hurricane Florence (2018) with L-Band Synthetic Aperture Radar, Commercial Imagery, and Ancillary Data via Random Forest Classification

Mapping the extent of floodwaters following extreme rainfall aids in the distribution of resources, recovery efforts, and damage assessment practices. Development of a land cover classification system focused on mapping inundation after major hurricane events using synthetic aperture radar (SAR) data could allow for the production of near-real-time inundation mapping, enabling government and emergency response entities to get a preliminary idea of a developing situation. In response to Hurricane Florence of 2018, NASA JPL collected numerous swaths of quad-pol L-band SAR data with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument observing the record-setting river stages across North and South Carolina. The resulting fully-polarized SAR images allow for mapping of inundation extent at a high spatial resolution with a unique advantage over optical imaging stemming from the sensor’s ability to penetrate cloud cover and dense vegetation. This study seeks to determine how accurately maps of inundation can be generated from L-band SAR imagery through Random Forest classification. Once the extent of water and inundated vegetation is classified, cleanup operations are performed using fuzzy logic to reduce false detections. Estimates of water extent are then combined with datasets describing the distribution of population, buildings, and roads throughout the domain to evaluate societal impacts. Results from the Hurricane Florence case study will be discussed along with the limitations of available validation data for assessment of the classifier’s accuracy.

Alexander Melancon↗

Hybrid LCA model for assessing the embodied environmental impacts of buildings in South Korea

The assessment of the embodied environmental impacts of buildings can help decision-makers plan environment-friendly buildings and reduce environmental impacts. For a more comprehensive assessment of the embodied environmental impacts of buildings, a hybrid life cycle assessment model was developed in this study. The developed model can assess the embodied environmental impacts (global warming, ozone layer depletion, acidification, eutrophication, photochemical ozone creation, abiotic depletion, and human toxicity) generated directly and indirectly in the material manufacturing, transportation, and construction phases. To demonstrate the application and validity of the developed model, the environmental impacts of an elementary school building were assessed using the developed model and compared with the results of a previous model used in a case study. The embodied environmental impacts from the previous model were lower than those from the developed model by 4.6–25.2%. Particularly, human toxicity potential (13 kg C{sub 6}H{sub 6} eq.) calculated by the previous model was much lower (1965 kg C{sub 6}H{sub 6} eq.) than what was calculated by the developed model. The results indicated that the developed model can quantify the embodied environmental impacts of buildings more comprehensively, and can be used by decision-makers as a tool for selecting environment-friendly buildings. - Highlights: • The model was developed to assess the embodied environmental impacts of buildings. • The model evaluates GWP, ODP, AP, EP, POCP, ADP, and HTP as environmental impacts. • The model presents more comprehensive results than the previous model by 4.6–100%. • The model can present the HTP of buildings, which the previous models cannot do. • Decision-makers can use the model for selecting environment-friendly buildings.

54 ENVIRONMENTAL SCIENCES↗

Measuring labor productivity dynamics in U.S. industrial and electric power sectors: a case study (2014–2023)

This study proposes a subsystem methodology for measuring labor productivity in the U.S. industrial and electric power sectors by leveraging public data available between 2014 and 2023. Building on Pasinetti’s framework and subsequent developments, the approach employs Vertically Integrated Sectors (VIS) to account for both direct and indirect productivity effects. The novelty of this work is twofold. First, it enables the estimation of productivity trends over time, providing a robust foundation for empirical analysis. Second, it applies the methodology to a case study of the electric generation sector, highlighting its practical relevance. Using data from the Bureau of Economic Analysis, the Bureau of Labor Statistics, and the Impact Analysis for Planning (IMPLAN) tool, the study reveals significant discrepancies between conventional productivity measures and those derived from the VIS approach. Furthermore, the proposed method aligns with the principles of Integrated Energy Systems by capturing the interrelations among generation, distribution, storage, and consumption. This alignment underscores its utility and applications for energy-related policy and planning. Overall, the findings contribute to more precise labor productivity assessments, supporting informed decision-making and future research. Additionally, the method highlights the importance of considering the whole supply chain, providing interrelated metrics for labor productivity which includes both, direct and indirect effects on the final labor productivity metric. By incorporating intersectoral dependencies, this method offers a more comprehensive and accurate measure of labor productivity compared to traditional metrics.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Experience curve development and cost reduction disaggregation for fuel cell markets in Japan and the US

Technology learning rates can be dynamic quantities as a technology moves from early development to piloting and from low volume manufacturing to high volume manufacturing. This work describes a generalizable technology analysis approach for disaggregating observed technology cost reductions and presents results of this approach for one specific case study (micro-combined heat and power fuel cell systems in Japan). We build upon earlier reports that combine discussion of fuel cell experience curves and qualitative discussion of cost components by providing greater detail on the contributing mechanisms to observed cost reductions, which were not quantified in earlier reports. Greater standardization is added to the analysis approach, which can be applied to other technologies. This paper thus provides a key linkage that has been missing from earlier literature on energy-related technologies by integrating the output of earlier manufacturing cost studies with observed learning rates to quantitatively estimate the different components of cost reduction including economies of scale and cost reductions due to product performance and product design improvements. This work also provides updated fuel cell technology price versus volume trends from the California Self-Generation Incentive Program, including extensive data for solid-oxide fuel cells (SOFC) reported here for the first time. The Japanese micro-CHP market is found to have a learning rate of 18% from 2005 to 2015, while larger SOFC fuel cell systems (200 kW and above) in the California market are found to have a flat (near-zero) learning rate, and these are attributed to a combination of exogenous, market, and policy factors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

PlanetSense: A Real-time Streaming and Spatio-temporal Analytics Platform for Gathering Geo-spatial Intelligence from Open Source Data

Geospatial intelligence has traditionally relied on the use of archived and unvarying data for planning and exploration purposes. In consequence, the tools and methods that are architected to provide insight and generate projections only rely on such datasets. Albeit, if this approach has proven effective in several cases, such as land use identification and route mapping, it has severely restricted the ability of researchers to inculcate current information in their work. This approach is inadequate in scenarios requiring real-time information to act and to adjust in ever changing dynamic environments, such as evacuation and rescue missions. In this work, we propose PlanetSense, a platform for geospatial intelligence that is built to harness the existing power of archived data and add to that, the dynamics of real-time streams, seamlessly integrated with sophisticated data mining algorithms and analytics tools for generating operational intelligence on the fly. The platform has four main components – i) GeoData Cloud – a data architecture for storing and managing disparate datasets; ii) Mechanism to harvest real-time streaming data; iii) Data analytics framework; iv) Presentation and visualization through web interface and RESTful services. Using two case studies, we underpin the necessity of our platform in modeling ambient population and building occupancy at scale.

big data architecture↗

Semi-Annual Report for Modular Integrated Gas High Temperature Reactor Development during Performance Period April 2022 - September 2022

Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multidisciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR in 3 years and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. Additionally, Argonne is providing analysis of the primary coolant system to ensure temperatures within the core remain below safety margins during steady-state and potential accident scenarios. This second semi-annual report summarized the progress made at Argonne on the two tasks during the second half of FY22. As a part of the RCCS design task, a scoping calculation in estimating HVAC capability for the HC-HTGR reactor building was performed. A water panel modeling study was first performed with the test case, which confirms the capability of the RELAP5-3D modeling approach to explore various design options of the HC-HTGR RCCS under consideration. Then, a reference RELAP5-3D model for the unit geometry of the preliminary design of the HC-HTGR RCCS was developed. A preliminary performance analysis was conducted to evaluate the performances of a single-phase natural circulation and panel conduction in various operating conditions. For the primary coolant system analysis task, preliminary thermal hydraulic analysis of the HC-HTGR core design was performed with a high resolution 1D fluid-3D solid coupled model using the System Analysis Module (SAM) to assess the assembly coolant channel and bypass flow mass flow rate distribution. Some preliminary work on the development of a full core reduced order model was discussed following the assembly level model to predict the core wide coolant flow distribution and to model certain operational and accidental transients.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Stochastic Optimization for Integration of Renewable Energy Technologies in District Energy Systems for Cost-Effective Use

Stochastic optimization of a district energy system (DES) is investigated with renewable energy systems integration and uncertainty analysis to meet all three major types of energy consumption: electricity, heating, and cooling. A district of buildings on the campus of the University of Utah is used as a case study for the analysis. The proposed DES incorporates solar photovoltaics (PV) and wind turbines for power generation along with using the existing electrical grid. A combined heat and power (CHP) system provides the DES with power generation and thermal energy for heating. Natural gas boilers supply the remaining heating demand and electricity is used to run all of the cooling equipment. A Monte Carlo study is used to analyze the stochastic power generation from the renewable energy resources in the DES. The optimization of the DES is performed with the Particle Swarm Optimization (PSO) algorithm based on a day-ahead model. The objective of the optimization is to minimize the operating cost of the DES. The results of the study suggest that the proposed DES can achieve operating cost reductions (approximately 10% reduction with respect to the current system). The uncertainty of energy loads and power generation from renewable energy resources heavily affects the operating cost. The statistical approach shows the potential to identify probable operating costs at different time periods, which can be useful for facility managers to evaluate the operating costs of their DES.

14 SOLAR ENERGY↗

Knowledge based systems: A critical survey of major concepts, issues and techniques. Visuals

This Working Paper Series entry represents a collection of presentation visuals associated with the companion report entitled, Knowledge Based Systems: A Critical Survey of Major Concepts, Issues, and Techniques, USL/DBMS NASA/RECON Working Paper Series report number DBMS.NASA/RECON-9. The objectives of the report are to: examine various techniques used to build the KBS; to examine at least one KBS in detail, i.e., a case study; to list and identify limitations and problems with the KBS; to suggest future areas of research; and to provide extensive reference materials.

Dominick, Wayne D.↗

Technology Solutions Case Study: Cost Analysis of Roof-Only Air Sealing and Insulation Strategies on 1-1/2 Story Homes in Cold Climates, Minneapolis, MN

This case study describes the External Thermal and Moisture Management System developed by the NorthernSTAR Building America Partnership. This system is typically used in deep energy retrofits and is a valuable approach for the roof-only portions of existing homes, particularly the 1 1/2-story home. It is effective in reducing energy loss through the building envelope, improving building durability, reducing ice dams, and providing opportunities to improve occupant comfort and health.

1 1/2-STORY HOUSE↗

Building the Foundation for Assessing GOM Offshore CO 2 EOR and CO 2 Storage [Slides]

This PowerPoint Presentation was used in a seminar given to headquarters personnel as well as other stakeholders. The seminar took place on August 7, 2020. The presentation introduces three offshore oil field case studies: Cognac, Petronius, and Horn Mountain. The NETL/ARI Gulf of Mexico (GOM) offshore large oil fields data base provides a strong foundation for the upcoming offshore GOM CO 2 storage and enhanced oil recovery (EOR) assessment. The three Case Studies show that significant volumes of CO 2 can be securely stored in the offshore GOM and that notable volumes of addition oil can be recovered from this area with CO 2 EOR. The Case Studies also show that the CO 2 Prophet Model can serve as an excellent assessment tool. The “next steps” include building the cost and economics models for offshore CO 2 transportation and particularly for conducting seafloor CO 2 EOR and CO 2 storage.

02 PETROLEUM↗

Cyber-Informed Engineering Power Generation Guide [Slides]

The CIE for Power Generation: Insights and Case Studies guide is being developed to assist engineers at utilities, asset owner-operators developers, and cybersecurity teams to build in robustness and cyber resiliency into their designs using cyber-informed engineering practices. This guide will break out these topics including use cases by chapters for areas such as Nuclear, IBRs, Geothermal, natural gas, etc.

97 MATHEMATICS AND COMPUTING↗

Modeling Thermal Interactions between Buildings in an Urban Context

Thermal interactions through longwave radiation exchange between buildings, especially in a dense urban environment, can strongly influence a building’s energy use and environmental impact. However, these interactions are either neglected or oversimplified in urban building energy modeling. We developed a new feature in EnergyPlus to explicitly consider this term in the surface heat balance calculations and developed an algorithm to batch calculating the surrounding surfaces’ view factors using a ray-tracing technique. We conducted a case study with a district in the Chicago downtown area to evaluate the longwave radiant heat exchange effects between urban buildings. Results show that the impact of the longwave radiant effects on annual energy use ranges from 0.1% to 3.3% increase for cooling and 0.3% to 3.6% decrease for heating, varying among individual buildings. At the district level, the total energy demand increases by 1.39% for cooling and decreases 0.45% for heating. We also observe the longwave radiation can increase the exterior surface temperature by up to 10 °C for certain exterior surfaces. These findings justify a detailed and accurate way to consider the thermal interactions between buildings in an urban context to inform urban planning and design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗