R&D for Safety Codes and Standards:Materials and Components Compatibility.
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ANSI/ASHRAE Standard 140 Method of Test for Evaluating Building Performance Simulation Software specifies the method to test the core competency of building performance simulation (BPS) software, a broad class of software which includes building energy modeling (BEM) software. Standard 140 has been widely used by BEM software vendors to help diagnose and compare the results from the program with other modeling programs. The Standard is also referenced by codes, standards, government programs, and other incentive programs as a part of minimum requirements for qualifying BEM software. The explanatory information, summary tables and figures in this 140 User’s Manual (referred to as “this Manual”) are provided to help users in implementing various suites of tests specified in Standard 140-2023 (referred to in this manual as “Standard 140” or “the Standard”).
Background Although data on industry and occupation (I&O) are important for understanding cancer risks, obtaining standardized data is challenging. This study describes the capture of specific I&O text and the ability of a web‐based tool to translate text into standardized codes. Methods Data on 62 525 cancers cases received from eight National Program of Cancer Registries (NPCR) states were submitted to a web‐based coding tool developed by the National Institute for Occupational Safety and Health for translation into standardized I&O codes. We determined the percentage of sufficiently analyzable codes generated by the tool. Results Using the web‐based coding tool on data obtained from chart abstraction, the NPCR cancer registries achieved between 48% and 75% autocoding, but only 12‐57% sufficiently analyzable codes. Conclusions The ability to explore associations between work‐related exposures and cancer is limited by current capture and coding of I&O data. Increased training of providers and registrars, as well as software enhancements, will improve the utility of I&O data.
The introduction of Zero Energy Ready Home Manufactured Homes (ZERH MH) qualification for manufactured homes has generated significant attention and interest in the industry to employ advanced manufacturing techniques. VEIC engaged with Titan Homes to create an advanced manufactured home design that employs ZERH standards, other client-driven above-code standards, and manufacturing processes improvements. This case study identifies specific energy-efficient and quality improvement measures that were implemented to achieve certification and take advantage of incentives for home manufacturers.
Building energy codes focus on building design, construction and renovation and have significantly increased building efficiency since the first national energy code was published in 1975. Most jurisdictions have energy codes based on ANSI/ASHRAE/IES Standard 90.1 (hereto referred to as Standard 90.1) and the International Energy Conservation Code (IECC). Compliance options available in these model energy codes include a prescriptive path, whole building performance paths – including IECC Total Building Performance (TBP), Standard 90.1 Energy Cost Budget (ECB) method and Performance Rating Method (PRM) – and system performance paths for envelope and heating, ventilation, and air-conditioning systems. Building performance standard (BPS) policies are an emerging policy tool used by jurisdictions to reduce the operational energy use or greenhouse gas (GHG) emissions of the existing commercial building stock. BPS policies vary widely between jurisdictions and are tailored to each location’s climate and energy goals. Intuitively, projects that met a recent edition of the energy code should comply with the BPS targets.
Building energy codes focus on building design, construction and renovation and have significantly increased building efficiency since the first national energy code was published in 1975. Most jurisdictions have energy codes based on ANSI/ASHRAE/IES Standard 90.1 (hereto referred to as Standard 90.1) and the International Energy Conservation Code (IECC). Compliance options available in these model energy codes include a prescriptive path, whole building performance paths – including IECC Total Building Performance (TBP), Standard 90.1 Energy Cost Budget (ECB) method and Performance Rating Method (PRM) – and system performance paths for envelope and heating, ventilation, and air-conditioning systems. Building performance standard (BPS) policies are an emerging policy tool used by jurisdictions to reduce the operational energy use or greenhouse gas (GHG) emissions of the existing commercial building stock. BPS policies vary widely between jurisdictions and are tailored to each location’s climate and energy goals. Intuitively, projects that met a recent edition of the energy code should comply with the BPS targets. However, some new buildings may struggle with meeting the BPS for the following reasons: 1. Energy codes focus on the design of the building and its projected ability to perform efficiently, while BPS compliance is dependent on the actual ongoing performance of the building, considering variables like occupancy, operation, and maintenance. 2. There are significant differences in the methodologies used to determine BPS compliance versus code compliance, including how each handles compliance metrics, handling of building amenities, and renewable energy generation. 3. The prescriptive compliance path in the energy code is based on performance of individual building components, as opposed to the performance compliance path which accounts for holistic building design strategies and interdependent building systems. This can result in a significant variability in post-occupancy performance for buildings built using the prescriptive path. Designs on the lower end of the permitted efficiency range may struggle with meeting the BPS.
The country’s first Zero Energy Ready manufactured home that is certified by the U.S. Department of Energy (DOE) is up and running in Russellville, Alabama. The manufactured home was built by a partnership between Southern Energy Homes and the Advanced Residential Integrated Energy Solutions Collaborative (ARIES), which is a DOE Building America team. The effort was part of a three-home study including a standard-code manufactured home and an ENERGY STAR® manufactured home. Cooling-season results showed that the building used half the space-conditioning energy of a manufactured home built to the U.S. Department of Housing and Urban Development’s (HUD’s) Manufactured Home Construction and Safety Standards. These standards are known collectively as the HUD Code, which is the building standard for all U.S. manufactured housing.
The Designs for Risk Evaluation and Management (DREAM) tool was developed as part of the effort to quantify the risk of geologic storage of carbon dioxide (CO 2 ) under the U.S. Department of Energy's National Risk Assessment Partnership (NRAP). DREAM is an optimization tool created to identify optimal monitoring schemes that minimize the time to first detection of CO 2 leakage from a subsurface storage formation. DREAM acts as a post-processer on user-provided output from subsurface leakage simulations. While DREAM was developed for CO 2 leakage scenarios, it is applicable to any subsurface leakage simulation of the same output format. The DREAM tool is comprised of three main components: (1) a Java wizard used to configure and execute the simulations, (2) a visualization tool to view the domain space and optimization results, and (3) a plotting tool used to analyze the results. A secondary Java application is provided to aid users in converting common American Standard Code for Information Interchange (ASCII) output data to the standard DREAM hierarchical data format (HDF5). DREAM employs a simulated annealing approach that searches the solution space by iteratively mutating potential monitoring schemes built of various configurations of monitoring locations and leak detection parameters. This approach has proven to be orders of magnitude faster than an exhaustive search of the entire solution space. The user's manual illustrates the program graphical user interface (GUI), describes the tool inputs, and includes an example application.
This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in an urbanized catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, distributed temperature sensing (DTS), continuous self-potential (SP) monitoring, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Field_Application subfolder contains the ATS XML input scripts, data files, output data for the SP site. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. The flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.m can only be used with COMSOL with MATLAB) is executed using the ATS output data to simulate the potential field. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) DTS Contains collated DTS data including raw Stokes and anti-Stokes measurement (provided as .h5 file). It also includes DTS processing.ipynb, a Jupyter notebook for calibrating the DTS data using dts_calibration Python package. cooler_calibration.csv is the DTS calibration CSV used in the calibration sequence. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion. 6) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 7) SP Contains the SP data collected in field at the SP sites (provided as CSV files). 8) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). Note: Code files (.ipynb, .py, .xml) can be opened in any standard code editor, .exo file can be viewed using Paraview, .h5 files can be opened using HDFView software and h5py Python package, and .resipy file can be opened with the open-source ResIPy software.