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Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

Automation of Vulnerability and Patch Management: Information Extraction, Association, and Optimization

Vulnerability and patch management is an integral part of a robust cybersecurity program, yet it grows increasingly complex due to the sheer amount of data that must be analyzed. Particularly in Operational Technology (OT) environments, analysis must be done manually because of the lack of automated solutions. Additionally, there are many steps in this process, from the initial discovery of the vulnerability to the implementation of its remediation, and each step in the process requires different data in order to be performed effectively. In this work, we provide approaches and strategies to assist operators in industrial or OT environments throughout the vulnerability management cycle. Security advisories provide key information about mitigation strategies, or actions that can be taken when a patch is unavailable or cannot be installed. Details of these strategies are not shared in public vulnerability databases and must be found manually. We approach this problem by designing a solution to automatically identify that information within vendor security advisories and retrieve it for operator use. We start with an approach that requires domain-specific knowledge of certain frequently-seen reference websites. Next, an approach that can work on an arbitrary website but relies on certain keywords. Finally, an approach that uses Natural Language Processing (NLP) methods and does not require specific knowledge or keywords. Each of these approaches is more general than its predecessor; we demonstrate high accuracy for all approaches Advisories also often contain details of affected products in non-standard or natural language formats. While this information can be easily understood when read by an operator, the non-standard format acts as a barrier to effective automation. We provide an approach for the first step in this process: identifying vendors in security advisories and mapping them to a standard framework for representing digital assets and software products. We evaluate five established string similarity algorithms, plus one of our own design that combines string similarity and information theory, on the task of mapping vendors to their corresponding entries in the Common Platform Enumeration (CPE) repository. Our results show that our proposed metric outperforms all others. Due to the constraints on time, finances, and personnel for organizations, Large Language Models (LLMs) may seem like attractive opportunities for security operators to speed up information gathering; however, it is still not clear whether LLMs can handle vulnerability management tasks well. To answer this question, we perform an empirical study of LLMs’ ability to provide consistent, accurate information about vulnerabilities in order to guide organizations in their adoption of LLMs. We observe poor performance for all models tested, suggesting that these models are not well-suited to the consistent retrieval of accurate vulnerability information. Finally, once vulnerabilities have been identified and any additional information has been obtained, operators must decide which remediation actions to implement based on their available resources. This already-complex problem becomes even more so when we consider that a vulnerability may have multiple avenues for remediation. We formulate this scenario as two knapsack problems and provide solutions, which we then compare against several existing strategies for vulnerability prioritization seen in real operational environments.

McClanahan, Kylie↗

Kivalina Biomass Reactor

This report summarizes work performed under DOE Award DE-EE00010149 to support the reliable operation of a community-scale biochar reactor system in Kivalina, Alaska. The project focused on improving sanitation and waste management in a remote community by assessing the installed system, identifying spare parts, defining key performance indicators (KPIs), preparing operator and maintenance manuals, and developing mobile reporting tools for operational data and KPI tracking. The team also produced training materials and recorded videos to support operator onboarding and continuity. The project demonstrated progress in system readiness, documentation, and digital reporting, while also identifying challenges common to remote deployments, including travel constraints, upstream system failures, and local resource limitations. This work provides a practical framework for improving the operation, monitoring, and future replication of biomass reactor systems in remote communities.

09 BIOMASS FUELS↗

Changes in SSL Device Efficiency and Optical Performance Under Accelerated Aging Conditions

Lighting application efficiency (LAE) describes the efficient delivery of light from the light source to the lighted task and is viewed as a new frontier—increasing energy savings with solid-state lighting (SSL) technologies. The framework for LAE that is proposed by the U.S. Department of Energy (DOE) consists of four major elements: light source efficiency, optical delivery efficiency, spectral efficiency, and intensity effectiveness. This report focuses on a sampling of the available SSL products that can be broadly defined as having modified spectral output because the method of spectra modification has a significant impact on light source efficiency and long-term optical delivery and spectral efficiencies. This report focused on the changes in light source, optical delivery, and spectral efficiencies that occur during aging of SSL devices. An accelerated stress test (AST) regiment was developed for the devices under test (DUTs) examined in this report to provide insights into how the performance of SSL devices change with aging. The AST protocols demonstrate that the SSL products discussed in this report often reduce light source efficiency to achieve different spectral characteristics. In addition, aging of the optical components (e.g., lenses, solder masks) in SSL devices can produce increased light absorption, which negatively impacts optical delivery efficiency and light source efficiency. The modified spectral outputs of the selected SSL products discussed in this report come in a variety of form factors and achieve enhanced optical performance by using a variety of methods. All of the products examined in this study use mid-power light-emitting diodes (MP-LEDs), although the number, configuration, phosphor content, and light-emitting diode (LED) pump of the MP-LEDs differ. Product MS-1 is a 60-watt (W) replacement A19 lamp with a hermetically sealed glass globe, which contains an embedded optical filter to absorb green and yellow emissions, thereby creating a “sunlike” modified spectrum. Product MS-2 is a 60-W replacement A19 lamp with 30 MP-LEDs, and it uses a violet LED pump, along with green and red phosphor emissions, to produce a “healthy” spectrum. This spectrum omits blue emissions in an effort to reduce melanopic lux. Product MS-3 is an LED module consisting of 21 MP-LEDs that use a violet LED pump, along with blue, green, and red phosphors, to produce a “sunlike” spectrum. Products MS-4 and MS-5 are both 6-inch (in) downlights that use a manual switching mechanism so that users can select application-specific correlated color temperatures before installation. Products MS-4 and MS-5 both contain two LED primaries (2,700 Kelvin [K] and 5,000 K) for spectral tuning. Product MS-4 contains 12 MP-LEDs for each LED primary, and Product MS-5 contains 10 MP-LEDs for each LED primary. This report summarizes the overall findings from up to 8,000 hours (hrs) of AST on the lamp DUTs (Products MS-1 and MS-2); up to 5,000 hrs of AST on the LED light engine DUTs (Product MS-3); and up to 7,000 hrs of AST on the downlight DUTs (Products MS-4 and MS-5). The AST procedures used in this study included a room temperature operational life (RTOL) test, an operational life test conducted at 45 degrees Celsius (°C; 45OL) test, an operational life test conducted at 75°C (75OL), a wet high-temperature operational life test performed at 65°C and 90% relative humidity (6590), and a wet high-temperature operational life test performed at 75°C and 75% relative humidity (7575). The AST procedures used for Products MS-1 and MS-2 were RTOL, 45OL, and 6590. The AST procedures used for Products MS-3, MS-4, and MS-5 were RTOL, 75OL, and 7575. During the ASTs described herein, separate populations of each product (three DUTs in each population for Products MS-1, MS-2, MS-4, and MS-5; four DUTs in each population for Product MS-3) were subjected to power cycling of 1 hr on and 1 hr off. The key findings from this study include the following. Enhanced optical performance came at the cost of reduced light source efficiency for the lamps and light engines examined in this study. The optical filter used to produce a “sunlike” spectrum for Product MS-1 reduced light source efficiency by 26%, from 113 lumens per watt (lm/W) to 85 lm/W. Products MS-2 and MS-3 that used a violet-pumped LED to achieve “healthy” and “sunlike” enhanced optical performance, respectively, suffered the largest reduction in initial light source efficiency (49 lm/W for Product MS-2 and 68 lm/W for Products MS-3) perhaps because of the use of violet LED as the optical pump. Product MS-2 also had the poorest color fidelity because of undersaturation of blues and oversaturation of greens and yellows. Chromaticity maintenance of the products in this study was generally good, with parametric failure only occurring for one product at one AST condition (i.e., Product MS-3 at 7575). The chromaticity shift for Product MS-3 in 7575 test conditions resulted from reduced emissions of the broad green and red phosphors used to mimic sunlight in the 500–750 nanometer (nm) range. As a result of these phosphor emission losses, chromaticity shifted toward the more stable violet-pumped LED and blue phosphor. Although chromaticity maintenance was acceptable for most products tested, different chromaticity shift mechanisms were observed for temperature and humidity tests compared with temperature alone for Products MS-1, MS-2, and MS-3. For Product MS-1, a relative increase in green emissions was observed with humidity, which may indicate humidity-accelerated degradation of the optical filter at green wavelengths (optical delivery efficiency reduction) or degradation of the emitters in the red region (spectral efficiency reduction). The violet-pumped products (i.e., MS-2 and MS-3) exhibited different chromaticity shift behavior in the temperature-humidity environments, with Product MS-2 shifting generally yellow because of photo-induced oxidation of the plastic globe (i.e., a reduction of optical delivery efficiency) and Product MS-3 shifting toward violet and blue emitters because of faster loss of emission from green and red phosphors (i.e., a reduction in spectral efficiency). Because of an initial drop in power consumption, the light source efficiency of downlights (Products MS-4 and MS-5) increased at RTOL throughout the test duration. The light source efficiency initially increased during 75OL until a decay in luminous flux maintenance (LFM) dominated light source efficiency, whereas the light source efficiency decreased for the entire 7575 test duration. It was found that increasing the ambient environment of an SSL device from 25°C to 75°C decreases the LFM by 2.7 to 5.5, depending on design of the SSL device. Adding humidity to the system (75OL to 7575) was found to decrease LFM by another factor of approximately 3.0. A common location of failure was identified for the downlights (Products MS-4 and MS-5) operated in the 7575 environment. This failure abruptly occurred between 3,000 to 5,000 hrs of testing on the film capacitor of the electromagnetic interference (EMI) filter near the diode bridge for 11 of the 12 downlights. It is likely that this failure was caused by a combination of the high electrical voltage across the capacitor, the location of the capacitor near the heat sources (e.g., transformers, diode bridges, power resistors), and the high stress environment of 7575. Longer test times are needed to fully understand the LFM, luminous efficacy changes, and chromaticity shifts for some of the products. Because of the high reliability, light source efficiency, and spectral tuning capabilities of LEDs, the expectations of LAE for SSL products are greatly increased over traditional lighting products. The data gathered in this report begin to provide an understanding of the tradeoffs that current SSL products undergo when optimizing the different efficiency elements of LAE. As discussed in this report, the findings from the tests conducted show that the optimization of spectral efficiency can come at the cost of initial light source efficiency. Furthermore, the introduction of violet LEDs can promote long-term optical delivery efficiency degradation, and the introduction of optical filters or new phosphors can lead to unwanted spectral efficiency changes because the ratio of phosphor emitters changes with aging. The data presented in this report also identified a common failure location in 6-in downlights. The results regarding long-term behavior of the modified spectra devices studied provide valuable information about changes to the light source, spectral, and optical delivery efficiencies as the devices age. This information can be used to improve future SSL designs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DRiFT - Release 1.0.0 Organic Scintillators

DRiFT (a Detector Response Function Toolkit) is LANL-developed software that postprocesses output from the extensively validated radiation transport code, MCNP [1], and generates realistic nuclear instrumentation response. DRiFT is designed to be flexible, enabling users to specify detector type and many experimental settings, as well as accommodating the addition of their own desired features. Although DRiFT development has included scintillator [2], gas [3], and semiconductor features [4], the focus of this release is on organic scintillator and associated capabilities. Organic scintillators are widely used in the areas of nuclear safeguards and nuclear non-proliferation efforts [5, 6]. DRiFT has several diagnostic and detector physics features relevant to detailed scintillator simulations including: tracking source particle information, scintillation light production, the effects of PMT quantum efficiency and gain, and digitizer settings. Users can select responses from many scintillator and PMT types supported natively by DRiFT, or add their own by following the instructions in this document. We acknowledge that DRiFT is under active development, bug reports and general questions and comments should be directed to Madison Andrews, madison@lanl.gov. This manual is divided into four parts: I) An overview of DRiFT, including how to obtain and install the executable, II) A description of the detector physics related to scintillators available, III) a description of more general DRiFT features the user may find useful, and IV) a description of the test suite and examples made available with the code release.

61 RADIATION PROTECTION AND DOSIMETRY↗

DRiFT - Release 1.1.1: Organic Scintillators

DRiFT (a Detector Response Function Toolkit) is LANL-developed software that postprocesses output from the extensively validated radiation transport code, MCNP, and generates realistic nuclear instrumentation response. DRiFT is designed to be flexible, enabling users to specify detector type and many experimental settings, as well as accommodating the addition of their own desired features. Although DRiFT development has included scintillator, gas, and semiconductor features, the focus of this release is on organic scintillator and associated capabilities. Organic scintillators are widely used in the areas of nuclear safeguards and nuclear non-proliferation efforts. DRiFT has several diagnostic and detector physics features relevant to detailed scintillator simulations including: tracking source particle information, scintillation light production, the effects of PMT quantum efficiency and gain, and digitizer settings. Users can select responses from many scintillator and PMT types supported natively by DRiFT, or add their own by following the instructions in this document. We acknowledge that DRiFT is under active development, bug reports and general questions and comments should be directed to Madison Andrews, madison@lanl.gov. This manual is divided into four parts: I) An overview of DRiFT, including how to obtain and install the executable, II) A description of the detector physics related to scintillators available, III) a description of more general DRiFT features the user may find useful, and IV) a description of the test suite and examples made available with the code release.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DRiFT - Release 2.1.0: Organic Scintillators and Gas Detectors

DRiFT (a Detector Response Function Toolkit) is LANL-developed software that post-processes output from the extensively validated radiation transport code, MCNP, and generates realistic nuclear instrumentation response. DRiFT is designed to be flexible, enabling users to specify detector type and many experimental settings, as well as accommodating the addition of their own desired features. The focus of this release is on organic scintillator, gas detector, and associated capabilities, while semiconductor features are still under development. Organic scintillators are widely used in the areas of nuclear safeguards and nuclear non-proliferation efforts. DRiFT has several diagnostic and detector physics features relevant to detailed scintillator simulations including: tracking source particle information, scintillation light production, the effects of PMT quantum efficiency and gain, and digitizer settings. Users can select responses from many scintillator and PMT types supported natively by DRiFT, or add their own by following the instructions in this document. DRiFT also has several diagnostic and detector physics features relevant to neutron gas detector simulations including: gas detector wall effects, inactive areas at the end of detector tubes, and effects of a preamplifier. We acknowledge that DRiFT is under active development, bug reports and general questions and comments should be directed to Madison Andrews, madison@lanl.gov. This manual is divided into four parts: I) An overview of DRiFT, including how to obtain and install the executable, II) A description of the detector physics related to scintillators available, III) a description of more general DRiFT features the user may find useful, and IV) a description of the test suite and examples made available with the code release.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Specifications of FIPD Fission Gas Release Data

All fission gas release data stored in the Fuels Irradiation & Physics Database (FIPD) was originally measured using the Gas Assay, Sample and Recharge (GASR) System in the Hot Fuel Examination Facility (HFEF). It is therefore called GASR data in FIPD. During the measurement of a sample, such as an irradiated EBR-II fuel element/capsule, a pinhole-sized region near the top of the element plenum was melted by a laser. Plenum gas then expanded into a calibrated volume (note: in this document, “sample” and “capsule/element” are used interchangeably consistent with GASR documents in FIPD). The pressure rise in the volume was recorded. Helium backfilling and expansion was then performed to determine the sample (e.g., fuel element plenum) volume using Boyle’s Law and assuming ideal gas behavior at constant temperature. With the plenum volume and the recorded pressure rise, the sample (e.g., fuel element plenum) pressure was derived with assumption of ideal gas law behavior. The plenum volume and pressure as well as the cladding temperature during the measurement were collected (GASR data in FIPD). Other records associated with the fission gas release data include: raw GASR data records including volumes and post-puncture pressures of seal head/sealing head and manifold, calibration data, backfilling gas pressure data, and the data analysis records. A sample(s) of the fission gas released from the plenum was collected by the GASR system into sample bottles. The chemical and isotopic composition of the gas sample was analyzed separately from GASR data, and will be discussed in a separate specification. The plenum volume, pressure, and cladding temperature during the measurement are typically utilized to determine the number of moles of gas in the plenum. This quantity is often compared to the number of moles of gas generated by fission events. However, calculating these values and their associated uncertainty is beyond the scope of this document, as it necessitates additional assumptions. The most important document to understand the FIPD fission gas data is the GASR operational manual (title: Gas Assay, Sample and Recharge System (GASR) operation and maintenance manual, HFEF/N OMM 4381, DOC. NO. W0018-0032-ES-00). This manual provides: (1) description of the GASR and the functions of each component (laser drilling, welding, seal head/sealing head, manifold, vacuum system, sample system, purge and gas tag system, etc.); (2) step-by-step guidance on calibrations, operations, and measurements; and (3) maintenance procedures and other details relating to the structure and operation of the GASR. Note that the original GASR operated until 2020. A new GASR with the same design and measurement methodology was installed in 2021. The specifications of the GASR presented on the HFEF website at this time are consistent with the ones given in the operational manual. The methods to calculate the plenum volume and pressures were not included in the operational manual, but were recorded in the legacy data analysis files. Details of the methods are given in Chapter 3.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Containerization in ATLAS Software Development and Data Production

The ATLAS experiment's software production and distribution on the grid benefits from a semi-automated infrastructure that provides up-to-date information about software usability and availability through the CVMFS dis-tribution service for all relevant systems. The software development process uses a Continuous Integration pipeline involving testing, validation, packag-ing and installation steps. For opportunistic sites that can not access CVMFS, containerized releases are needed. These standalone containers are currently created manually to support Monte-Carlo data production at such sites. In this paper we will describe an automated procedure for the containerization of AT-LAS software releases in the existing software development infrastructure, its motivation, integration and testing in the distributed computing system.

97 MATHEMATICS AND COMPUTING↗

VERAView User's Manual

VERAView has been developed as an interactive graphical interface for the visualization and engineering analyses of output data from VERA. The Python-based software is easy to install, intuitive to use, and provides instantaneous 2D and 3D images, 1D plots, and alpha-numeric data from VERA multi-physics simulations. This document provides a brief overview of the software and some description of the major features of the application, including examples of each of the encapsulated “widgets” that have been implemented thus far. VERAView is still under major development and large changes in the software and this document are still anticipated.

97 MATHEMATICS AND COMPUTING↗

Spatial Study 2021: Sensor-Based Time Series of Surface Water Temperature, Specific Conductance, Total Dissolved Solids, pH, and Dissolved Oxygen from across Multiple Watersheds in the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. The dataset provides two-hour time series hydrological and water chemistry sensor data, manual chamber open channel respiration data, handheld sensor water chemistry data, river substrate grain size photos, general environmental context photos, and field metadata (including qualitative information on instream and river corridor characteristics) collected during the same two-week period at 47 sites within multiple rivers throughout the Yakima River Basin in Washington, USA. Grain size photos can be used to improve estimates of channel substrate D50 data. Related sample-based water chemistry data are published separately at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1898914.This dataset is comprised of four main folders, one containing three sensor-specific subfolders and the others containing photographs. The SFA_SpatialStudy_2021_SensorData main data folder includes file-level metadata (FLMD), data dictionary (dd), installation methods, field metadata, Ultrameter water chemistry data, field data collection protocols, international generic sample number (IGSN) mapping file, and a readme file. The “Sensor_Manual_Specifications” subfolder contains pdf files from the manufacturer of each sensor with details on the sensor specifications. Each sensor subfolder (BarotrollAtm, MantaRiver, and MinidotManualChamber) contains a sensor data subfolder for timeseries data and a subfolder for plots and summary statistics. The BarotrollAtm Data subfolder contains In Situ Rugged BaroTROLL pressure and temperature data. The MantaRiver Data subfolder contains Eureka Manta+ 35B multisonde temperature, specific conductance, and pH data. The MinidotManualChamber Data subfolder contains PME MiniDOT Logger dissolved oxygen (mg/L and percent saturation) and temperature data. The folder SFA_SpatialStudy_2021_EnvironmentalContextPhotos contains environmental context photographs and videos. The folders SFA_SpatialStudy_2021_SedimentQuadratPhotos_Part1 and SFA_SpatialStudy_2021_SedimentQuadratPhotos_Part2 contain sediment quadrat photographs. All files are .csv, .pdf, .R, .jpg, .jpeg, .mp4, or .mov. This data package was originally published September 2022. It was updated January 2023 (modified files) and June 2024 (new and modified files). See the change history in data package readme for more details.We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

Satellite Imagery of PV Site Storm Damage

"This repository contains multiple data sets focused on visible damage to photovoltaic (PV) installations following extreme weather events such as hailstorms and hurricanes. Data sets are split into two categories: the first category, the ‘manually labeled’ data, was compiled by researchers manually, and contains manually identified PV sites exposed to storms. The second data set, the ‘aggregated’ data, is a compilation of the manually labeled PV sites and deep learning-identified PV sites. The hail damage data set focuses on post-storm PV damage following a September 24, 2023 hailstorm in Austin, TX, which caused over $600 million in damages in the Austin metro area. The hurricane damage data set focuses on post-storm PV damage following Hurricanes Irma and Maria in Puerto Rico and the US Virgin Islands. Hurricanes Irma and Maria were back-to-back category 5 hurricanes, which pummeled the Caribbean and southeastern United States in September 2017, causing an estimated $115.2 billion in damages."

14 SOLAR ENERGY↗

Force-triggered, Bio-based, Sealants for Prefabricated Building Components: Towards Improved Efficiency, Performance and Sustainability

The prefabricated building construction industry has made extensive progress in expediting the manufacture of prefabricated components at offsite plants. However, this progress has not translated to the assembly of the prefabricated components at the construction site. Case in point, sealing the joints between components to prevent air leaks requires the manual application of tape, caulk, or spray foam at the jobsite, and performance is highly dependent on the skills of the installer. To reduce assembly time and improve the airtightness and waterproofness of prefabricated components, we developed a sealant that can be installed at the plant and have its curing reaction triggered at the jobsite. Additionally, we used this opportunity to explore the use of bio-based feedstocks that are abundant and not used for food. We evaluated a series of force-triggered, bio-based, high strength, and fast curing sealants, consisting of a one-part heterogeneous system. These sealants are derived from formulations with ≥80% of bio-based components, consisting of a cardanol derived diepoxy that is microencapsulated in a polymer shell and embedded in a cardanol derived amine curing agent. The microcapsule shell allows separation of the reactive species in the one-part sealant allowing a fast-curing system to remain unreacted until the right trigger is applied. When the microcapsules are activated and broken by force, the highly reactive species mix and cure, exhibiting peel strengths up to 143 ppi. The open-air shelf stability of the sealant complexes was demonstrated by peel strength values of ~16 ppi when triggering the curing reaction even after being exposed for 8 months to open air and humidity. The successful on-demand triggering of curing reactions and the shelf stability provide efficacy of these force-triggered sealants for installation on prefabricated components, storage for months prior to delivery, and assembly at the jobsite. These force-triggered bio-based sealants for prefabricated buildings could result in lower installation time and cost as well as better performance than tapes and caulks at the jobsite.

Cortes Guzman, Karen [ORNL] (ORCID:000000028793468↗

Force-triggered, Bio-based, Sealants for Prefabricated Building Components: Towards Improved Efficiency, Performance and Sustainability

The prefabricated building construction industry has made extensive progress in expediting the manufacture of prefabricated components at offsite plants. However, this progress has not translated to the assembly of the prefabricated components at the construction site. Case in point, sealing the joints between components to prevent air leaks requires the manual application of tape, caulk, or spray foam at the jobsite, and performance is highly dependent on the skills of the installer. To reduce assembly time and improve assembly quality of prefabricated components, we developed a sealant that can be installed at the plant and triggered at the jobsite. Additionally, we used this opportunity to lower the use of fossil fuel derived feedstocks and introduced bio-based alternatives to decrease the embodied carbon of the new sealant. We evaluated a series of force-triggered, bio-based, high strength, and fast curing sealants, consisting of a one-part heterogeneous system. These sealants are derived from formulations with ≥80% of biogenic carbon, consisting of a cardanol derived diepoxy that is microencapsulated in a polymer shell and embedded in a cardanol derived amine curing agent. The microcapsule shell allows separation of the reactive species in the one part sealant allowing shelf stability to an otherwise fast curing system. When the microcapsules are broken and activated by force, the highly reactive species mix and cure, exhibiting peel strengths up to 143 ppi. The shelf stability of these sealants and the on-demand triggering of the curing reactions enable installation on prefabricated components and storage prior to delivery and assembly at a jobsite, which could result in consistent sealant application with lower installation time than tapes and caulks at the construction site.

Cortes Guzman, Karen [ORNL] (ORCID:000000028793468↗

S AP F LOWER : an automated tool for sap flow data preprocessing, gap-filling, and analysis using deep learning

Sap flow, a critical process in plant water use and ecosystem water cycles, is often measured using thermal dissipation probes (TDP) due to their ease of installation and continuous data collection. However, sap flow data frequently include noise, outliers, and gaps, creating challenges for analysis and requiring substantial manual processing. We developed S AP F LOWER , a tool that automates data preprocessing, model training, gap-filling, sapwood area scaling and modeling, and water use analysis. It integrates autocleaning, machine learning and deep learning models (e.g. random forest, Gaussian process regression, long short-term memory (LSTM), bidirectional LSTM (BiLSTM)), and efficient workflows to process sap flow data. S AP F LOWER can remove over 90% of noisy data while preserving legitimate variations and achieve high accuracy in gap-filling based on user-determined parameters. Random forest, LSTM, and BiLSTM models reduced root mean square error to 10% or less for long-term gaps. Model training and prediction can be performed efficiently within seconds. S AP F LOWER significantly enhances the efficiency and accessibility of TDP data analysis by automating complex tasks, enabling researchers without programming expertise to employ advanced techniques. Future improvements will focus on species-specific corrections for TDP and support for additional measurement methods. S AP F LOWER is openly available on GitHub (https://github.com/JiaxinWang123/SapFlower) and Zenodo (doi: 10.5281/zenodo.13665919).

ecosystem water balance↗

Pressure Transducer Measurement Variability in Deep Wells Screened Across the Water Table

Abstract Automated water level measurements collected using vented pressure transducers in deep wells screened across the water table may exhibit a greater response to barometric pressure changes than the true water level. The cause was hypothesized to be disequilibrium in barometric pressure between the wellbores and land surface due to air exchange with the deep vadose zone. In this study, vented and nonvented pressure transducers were installed and operated simultaneously in two deep wells screened across the water table. A vent tube open to the atmosphere at land surface allowed for barometric compensation of the vented transducers. Two nonvented transducers were installed in each well, one submerged in the water and one above the water surface. The difference in readings allowed for barometric compensation. Manual measurements were also collected. It was confirmed that measurements from the vented transducers exhibited greater variability in response to barometric pressure changes than the nonvented transducers and manual measurements. Comparison of the downhole barometric pressure measurements to values from a nearby meteorology station showed the response in the wells to changes in barometric pressure was time‐lagged and attenuated. Thus, the reference pressure from land surface supplied to the vented transducers was not representative of the air pressure within the wells. This caused fluctuations of the transducer readings in response to barometric pressure changes to be greater than the true water level change. This issue can be resolved by the use of nonvented pressure transducers.

McDonald, John P.↗

The Impact of Wall Control Performance on Connected Lighting Systems

Wall controls form the only touchpoint for individual room users and that room’s lighting control system. As such, these interfaces strongly influence user understanding and utilization of the system, as well as overall acceptance. The Next Generation Lighting Systems (NGLS) program began an evaluation of the wall controls in 14 connected lighting systems installed in various rooms of the NGLS Living Lab at Parsons School of Design in New York City. These systems demonstrate the wide range of approaches to wall control setup and functionality taken by manufacturers. Characterizing the 14 controls across six attributes, only four, or 29%, were identical. Requirements for wall control design were not specified explicitly by NGLS. Rather, wall controls were required to provide system performance according to three criteria: vacancy control (manual on/auto off) of two zones; manual continuous dimming of the same two zones; and an AV presentation mode in one of the two zones. This report examines the classification of entries, the assessment method used to evaluate the systems from installation through day-to-day use, and the system performance observed to date for each.

42 ENGINEERING↗