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At least 217 records · Page 12

Sensor Placement Optimization Study for the Built Environment: Next Steps Report

Systems of fixed-position radiation sensors can provide information that assists emergency responders following nuclear incidents. First responder organizations that implement systems of fixed-position sensors face numerous decisions regarding sensor selection, quantity, and placement. Researchers at Pacific Northwest National Laboratory (PNNL) have evaluated the performance of several hypothetical sensor systems during a simulated activation of a radiological dispersal device. Due to technical limitations, PNNL’s analysis was limited to a single location and number of scenarios. This document describes additional research and analysis that would result in improved guidance to first responder organizations considering installation of radiation monitoring systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Does manganese influence grass litter decomposition on a Hawaiian rainfall gradient?

Plant litter is a well-defined pool of organic matter (OM) in which the influence of manganese (Mn) on decomposition (both decomposition rate and the mix of compounds ultimately transferred to soil OM) has been clearly demonstrated in temperate forests. However, no similar study exists on grasslands and the effect of foliar Mn versus soil-derived Mn on litter decomposition is poorly known. We used a 5-month and 12-month field, and 10-month laboratory experiments to evaluate litter decomposition on the Kohala rainfall gradient (Island of Hawai‘i) in areas with different foliar and soil Mn abundances, and on which a single plant species (Pennisetum clandestinum) dominates primary production and the litter pool. The chemical imaging analyses of decomposed litter revealed that Mn 2+ oxidized to Mn 3+ and Mn 4+ on grass litter during decompositions—hallmarks of Mn-driven litter oxidation. However, these transformations and Mn abundance did not predict greater litter mass loss through decomposition. These observations demonstrate that the importance of Mn to an ecosystem’s C cycle does not rely solely on the metal’s abundance and availability.

54 ENVIRONMENTAL SCIENCES↗

Plug-in Electric Vehicle Charging Response Characterization for Grid Integration: Implications for Smart Charge Management

The rapid expansion of plug-in electric vehicles (PEVs) has created a unique challenge for electrical grids due to their significant power demand. At the same time, PEVs also create a unique opportunity to ease their own burden on the power grid, as they create a growing fleet of distributed energy resources capable of providing grid services such as demand response, frequency regulation, and renewable balancing. For aggregators and grid operators to effectively integrate PEVs into grid management, it is essential to first understand and characterize how they would respond in such situations. This study examines 25 models of PEVs across 25 makes, spanning model years from 2013 to 2025, to characterize their responses to the basic controls used in vehicle-grid integration (VGI): stopping, starting, and modulating the charge rate. Each vehicle was tested in a controlled laboratory setting to evaluate its performance in response to varying the maximum allowable current via the SAE J1772 control pilot signal, as well as its response to wake-up commands outlined in SAE J1772. Results show measurable differences across vehicle makes in the accuracy, latency, and precision with which PEVs respond to changes in ampacity, as well as varying sleep and wake-up behavior. The test results show that all vehicles respond to changes in ampacity, though with varying accuracy, precision, latency, and resolution. Wake-up behavior also differs across makes and models. These findings indicate that effective grid integration strategies must account for these differences. The results provide a foundation for understanding current vehicle behavior and advancing smart-charging methods while also highlighting the need for further testing, broader standardization, and manufacturer collaboration to ensure the successful integration of PEVs into the electrical grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Manufacturability and performance response of developed Ni-based alloys for reactor environments

Under the Advanced Materials and Manufacturing Technologies program, two Ni-based alloys fabricated by laser powder bed fusion (LPBF) at Oak Ridge National Laboratory and by laser powder directed energy deposition (LP-DED) at Idaho National Laboratory have been evaluated: γ′-strengthened Haynes 282 and solution-strengthened Inconel 625. Printing defects were observed in the LPBF 282 alloy fabricated using a Renishaw AM250 machine, likely due to particle spattering during printing. For both the LPBF and LP-DED 282 alloys, annealing at 1,180°C for 1 h resulted in partial recrystallization and a bimodal grain distribution, and subsequent aging for 4 h at 800°C led to the formation of a high density of nano-size γ′-strengthening precipitates. Creep testing performed at 750°C revealed lower creep life and ductility for the LPBF and LP-DED 282 compared with wrought 282. X-ray computed tomography combined with optical and scanning electron microscopy microstructural characterization revealed crack formation in the LPBF 282 alloy during creep testing, initiated either from printing defects or from creep cavitation at grain boundaries. Creep cavitation and cracking at grain boundaries were also observed for the LP-DED 282 alloy, and optimization of the printing strategies and postheat treatments will be needed to fabricate high-performance 282 components for high-temperature nuclear applications.

36 MATERIALS SCIENCE↗

Whole Algae Hydrothermal Liquefaction and Upgrading: A review of progress and challenges and insight into the future

This report summarizes the research at Pacific Northwest National Laboratory (PNNL) to evaluate the economic viability and environmental impact of using microalgae to produce fuels and other products via hydrothermal liquefaction (HTL). Over the past several years, PNNL has examined key aspects of feedstock cost and availability, formatting and conversion techniques, and the utilization of all HTL products. Investigations of feedstock cost led to opportunities to work with cost-advantaged algal feedstocks that can be provided at minimal cost for HTL processing. Cost-advantaged algae include wastewater-grown algae and harvested algal blooms. Although farm-cultivated algae offer the best possible biomass composition and scalability for HTL processing, the cost of the feedstock is too high to yield an economically competitive biofuel. Processing cost-advantaged feedstocks creates other unique challenges in adapting HTL to upgrade biomass with higher than typical ash content and less preferred composition (low lipid). Despite the challenges, HTL of cost-advantaged algae results in economically competitive pricing scenarios and significant advantages in reducing net emissions below 70% of the petroleum baseline. The utilization of a variety of potential non-fuel products from algal HTL, such as the use of HTL solids as a cement additive, provides a significant reduction in net emissions by offsetting emissions from other carbon-intense products. This report presents an analysis of the research conducted at PNNL to develop an economically and environmentally beneficial process for algae HTL.

09 BIOMASS FUELS↗

Queue wait time prediction in high performance computing (HPC) systems

High Performance Computing (HPC) systems are critical enablers for groundbreaking scientific research across various domains. Efficient resource allocation, facilitated by job scheduling, is paramount for maximizing the utilization of HPC systems. However, the variability in wait times for queued jobs poses challenges for users, necessitating accurate job wait time estimation. This paper explores the influence of job characteristics, including job size (the number of nodes requested and walltime), the queue to which the job is submitted and other resource requirements, on job wait times in leadership-class HPC systems. Focusing on the Theta Cray XC40 and Polaris machines at Argonne National Laboratory, the study evaluates the performance of different supervised learning algorithms in predicting job wait times. It also evaluates the impact of data preprocessing, including outlier detection, Principal Component Analysis (PCA), and feature selection, on the performance of wait time prediction models. The findings reveal insights into the relationship between job characteristics and wait times, offering a foundation for optimizing resource allocation and enhancing user experience. The methodologies and tools developed in this study are adaptable to other leadership-class HPC systems, providing a valuable contribution to the broader HPC community aiming to improve job scheduling efficiency and user satisfaction.

Okafor, Nwamaka↗

Development and field demonstration of residential air source integrated heat pump using a three-stage compressor

To promote decarbonization and all electrification at residential sectors, it is necessary to use air source heat pumps (ASHPs) to replace natural gas for space heating and water heating. ASHPs are widely utilized for residential space cooling, heating, and water heating due to their simplicity and cost-effectiveness. However, their performance can be compromised in cold climates, where they may experience reduced heating capacity. A multi-functional heat pump, using a single compressor, to meet all home space conditioning and water heating demands, is an emerging technology. To address this limitation, we have developed and demonstrated an air source integrated heat pump to fulfill comprehensive home comfort requirements. This system employs a three-stage compressor and a single set of heat exchangers and valves, optimizing functionality while minimizing costs. The performance of the developed system was rigorously evaluated in both laboratory and field settings. In laboratory conditions, the system achieved a Seasonal Energy Efficiency Ratio of 17.0 (average COP of 4.98) and a Heating Seasonal Performance Factor of 11.0 (3.22). Additionally, in its most efficient operational mode—combining space cooling and water heating—the unit attained a total energy efficiency exceeding 7.0 seasonal COP in the field and could heat a 189-liter tank of water in just 25 min. The field study corroborated the laboratory findings, validating the system’s performance in real-world conditions. Here, this integrated heat pump represents an ideal solution for decarbonizing homes in northern climates by providing efficient space heating and water heating, thereby replacing the need for natural gas.

Integrated heat pump↗

In situ reductive dissolution to remove Iodine-129 from aquifer sediments

The use of an aqueous reductant (Na-dithionite) with pH buffer (K-carbonate, pH 12) was evaluated in this laboratory study as a potential remedial approach for removing Fe oxide associated iodine and enhancing pump-and-treat extraction from iodine-contaminated sediments in the unconfined aquifer in the 200 West Area of the Hanford site. X-ray fluorescence data of untreated sediment indicated that iodine was largely associated with Fe (i.e., incorporated into Fe oxides), however, XANES data was inconclusive as to valence state. During groundwater leaching, aqueous and adsorbed iodine was quickly released, then additional iodine was slowly released potentially from dissolution of one or more surface phases. The Na-dithionite treatment removed greater iodine mass (2.9x) at a faster rate (1 to 4 orders of magnitude) compared to leaching with groundwater alone. Iron extractions for untreated and treated sediments showed a decrease in Fe(III)-oxides, which likely released iodine to aqueous solution. Solid phase inorganic carbon and aqueous Ca and Mg analysis further confirmed that significant calcite dissolution did not occur in these experiments meaning these phases did not release significant iodine. Although it was expected that, after treatment, 127 I concentrations would eventually be lower than untreated sediments, leaching experiments showed continued, elevated iodine concentrations for treated samples over 750 hours. Stop flow events during 1-D column leaching suggested that some iodide precipitated within the first few pore volumes. In the survey of metals during leaching, some silver was detected which could have been solubilized by the elevated pH of initial Na-dithionite injection. Then, silver (or other metals) could have subsequently precipitated with iodide during the initial stop flow event forming a slowly dissolving source. Although significantly greater iodine is removed with treatment, the long-term leaching needs to be investigated further as it may limit dithionite treatment at the field scale.

54 ENVIRONMENTAL SCIENCES↗

High-temperature high-pressure microfluidic system for rapid screening of supercritical CO 2 foaming agents

CO 2 foam helps to increase the viscosity of CO 2 flood fluid and thus improve the process efficiency of the anthropogenic greenhouse gas’s subsurface utilization and sequestration. Successful CO 2 foam formation mandates the development of high-performance chemicals at close to reservoir conditions, which in turn requires extensive laboratory tests and evaluations. This work demonstrates the utilization of a microfluidic reservoir analogue for rapid evaluation and screening of commercial surfactants (i.e., Cocamidopropyl Hydroxysultaine, Lauramidopropyl Betaine, Tallow Amine Ethoxylate, N,N,N' Trimethyl-N'-Tallow-1,3-diaminopropane, and Sodium Alpha Olefin Sulfonate) based on their performance to produce supercritical CO 2 foam at high salinity, temperature, and pressure conditions. The microfluidic analogue was designed to represent the pore sizes of the geologic reservoir rock and to operate at 100 °C and 13.8 MPa. Values of the pressure drop across the microfluidic analogue during flow of the CO 2 foam through its pore network was used to evaluate the strength of the generated foam and utilized only milliliters of liquid. The transparent microfluidic pore network allows in-situ quantitative visualization of CO 2 foam to calculate its half-life under static conditions while observing if there is any damage to the pore network due to precipitation and blockage. The microfluidic mobility reduction results agree with those of foam loop rheometer measurements, however, the microfluidic approach provided more accurate foam stability data to differentiate the foaming agent as compared with conventional balk testing. The results obtained here supports the utility of microfluidic systems for rapid screening of chemicals for carbon sequestration or enhanced oil recovery operations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Alloying of Pu-Al with Stainless Steel for Material Disposition

The Savannah River National Laboratory (SRNL) has evaluated several options for the disposition of stainless-steel clad plutonium metal alloy. One of the technologies under consideration is alloying of the material with stainless steel (SS). The resulting SS-Pu alloy would be a non-proliferable waste form consisting of a secondary Pu composition region microencapsulated in the refractory stainless steel. Two 8-kg ingots were made at SS-1.8Zr-0.4Pu alloys (wt %); 8 kg was determined in a previous study to be the maximum mass of SS ingot at the maximum target Pu loading of 350-g that would result in a SS-4.4Pu alloy (wt %). Two smaller 500-g ingots were also produced at SS-1.6Zr-1.4Pu and SS-1.4Pu (wt %). The 500-g ingots evaluated alloying at a higher Pu concentration than in the 8 kg ingots, and they evaluated the necessity of adding Zr metal to incorporate the Pu and control Pu oxidation. Zr addition was found to be unnecessary to incorporate the Pu and control Pu oxidation. Drill turnings were collected from the large and small ingots and metallographic samples were directly cut from the small ingots. Both were analyzed to validate the structure and composition region formation. Chemical analyses of turnings proved that the Pu was dispersed within the SS ingots.

36 MATERIALS SCIENCE↗

A Mobile Edge Computing Framework for Traffic Optimization At Urban Intersections Through Cyber-Physical Integration

The stop-and-go traffic pattern on urban roads often results in excessive energy consumption because of unnecessary vehicle braking, idling, and accelerations. With the widespread and increased use of automobiles, this traffic pattern creates many negative impacts (e.g., delayed travel time, air pollution, and additional carbon emission) on the sustainability of our cities. Taking advantage of the recent emerging Internet of Things (IoT) and edge computing paradigms, we propose a mobile edge computing framework that integrates the capability of real-time vehicle-to-infrastructure communication and intelligent speed optimization algorithms into a mobile app to optimize individual vehicles' driving speed at signalized intersections. The optimization aims to mitigate the stop-and-go traffic pattern and its undesirable consequences in urban transportation systems. The framework consists of (1) a cyberinfrastructure-enabled dynamic messaging system for retrieving and delivering real-time traffic and signal phase and timing information from IoT-connected signal controllers and sensors, (2) a real-time speed optimization algorithm for generating intelligent speed advisory using vehicle's information (e.g., GPS and driving directions from mobile sensing) and corresponding signal and traffic information, and (3) an ad-hoc mobile computing environment that converts drivers' smartphones into edge devices to host the speed optimization algorithms for enabling intelligent advisory on the vehicle's driving speed within signalized corridors. The paper presents the design and implementation of the proposed framework. Finally, we demonstrate the feasibility, usefulness, and energy-saving benefits of our proposed framework and its prototyping mobile app on urban transportation systems through traffic simulation, real-vehicle laboratory experiments, an evaluative survey, and field communication tests. The simulation-based energy evaluation results show that the 100% usage of the mobile app can achieve 24% energy savings in the transportation system.

33 ADVANCED PROPULSION SYSTEMS↗

Resource selection and species interactions between native and non‐native fishes in a simulated stream system

Abstract Effective fishery management necessitates understanding of resource partitioning by fishes that inhabit complex systems composed of biotic and abiotic features. Evaluations of non‐native species introductions have continually demonstrated adverse effects associated with abundance and distribution of native fishes. Therefore, understanding resource selection and interactions between native and non‐native species is important for recovery efforts. Habitat use by two native fish species (largescale sucker Catostomus macrocheilus [Girard] and mountain whitefish Prosopium williamsoni [Girard]) and one non‐native fish species (pumpkinseed Lepomis gibbosus [Linnaeus]) of the Kootenai River, Idaho, were evaluated in a laboratory stream system. Trials were conducted in allopatry and in sympatry with and without the presence of wood to describe habitat selection in the context of on‐going habitat rehabilitation efforts. Interactions were evident between native largescale sucker and non‐native pumpkinseed concerning use of a woody structure and current velocity. Mountain whitefish used low‐velocity habitats and selected locations that were further from wood when in sympatry with pumpkinseed. Our research suggests that habitat use of native, large‐river fishes may be influenced by the presence of a non‐native species, and that considering such interactions is critical when designing and implementing habitat rehabilitation efforts in river ecosystems.

Branigan, Philip R.↗

Thermal Aging Effects on the Yield and Tensile Strength of 9Cr-1Mo-V (Grade 91)

The long-term exposure of 9Cr-1Mo-V (Grade 91) steel to elevated temperature can have a significant effect on reducing its yield and tensile strength. The yield and tensile strength changes, in turn, have potential implications to the assurance of the integrity of components constructed with this material over their design or intended lifetime. The ASME Boiler & Pressure Vessel Code (BPVC), Section III, Division 5 (III-5, high temperature reactors) provides tabulated reduction factors for Grade 91 yield and tensile strength as a function of exposure temperature and time up to 300,000 h. ASME BPVC III-5 s intent to extend these factors to an exposure duration of 500,000 h, the lack of available historic information to support the existing factors, and the recent development of a physics-based prediction model for ASME BPVC application are prime motivation for this study. This work describes results of the conventional time-temperature Hollomon–Jaffe parameter, strength reduction ratio prediction method using an updated, extensive Grade 91 unaged and related aged material strength database. The method, previously used by Oak Ridge National Laboratory in its evaluation of Grade 91 and likely used in development of the existing BPVC III-5 reduction factors, provides strength reduction ratio predictions useful for general component fitness-for-service assessments and for computing BPVC III-5 reduction factors as defined. Specific reduction factors to 500,000 h at 650 °C applicable to ASME BPVC III-5 are computed from the strength reduction ratios.

36 MATERIALS SCIENCE↗

CHARM-SYCL: New Unified Programming Environment for Multiple Accelerator Types

Addressing performance portability across diverse accelerator architectures has emerged as a major challenge in the development of application and programming systems for high-performance computing environments. Although recent programming systems that focus on performance portability have significantly improved productivity in an effort to meet this challenge, the problem becomes notably more complex when compute nodes are equipped with multiple accelerator types—each with unique performance attributes, optimal data layout, and binary formats. To navigate the intricacies of multi-accelerator programming, we propose CHARM-SYCL as an extension of our CHARM multi-accelerator execution environment [27]. This environment will combine our SYCL-based performance-portability programming front end with a back end for extremely heterogeneous architectures as implemented with the IRIS runtime from Oak Ridge National Laboratory. Our preliminary evaluation indicates potential productivity boost and reasonable performance compared to vendor-specific programming system and runtimes.

Fujita, Norihisa↗

A subdermal tagging technique for juvenile sturgeon using a new self-powered acoustic tag

Abstract Background A new technology for a self-powered acoustic tag (SPT) was developed for active tracking of juvenile fish, intended to avoid the typical battery life constraints associated with active telemetry technology. We performed a laboratory study to evaluate a subdermal tagging technique for the SPT and effects of the tag on survival, tag retention, and growth in juvenile white sturgeon ( Acipenser transmontanus ). Results Survival was associated with tag retention. White sturgeon implanted with the SPT ( n = 30) had 93% survival and tag retention by day 28, 67% by day 101, and 38% by day 595 post-tagging. Sturgeon implanted with a passive integrated transponder (PIT) tag only (control group) had 96% survival and tag retention by day 28, and through day 101 post-tagging. Fish in the PIT group were repurposed after day 101, so no comparisons with this group were made at day 595 post-tagging. Specific growth rate (SGR) for fork length was a median of 0.25% day −1 by day 28 for the SPT group, which was significantly lower than the PIT group (median: 0.42% day −1 ; n = 27). The SPT and PIT groups had similar SGR fork length by day 101 post-tagging (0.22 and 0.25% day −1 , respectively). SGR weight was also lower for the SPT group compared to the PIT group on day 28 (1.39 and 2.11% day −1 , respectively), but the difference again dissipated by day 101 (0.79 and 0.88% day −1 , respectively). Conclusion The tagging technique and placement of the SPT allowed the tag to remain upright along the flank of the sturgeon to ensure maximum battery output of the SPT; however, retention rates of the SPT were not ideal. We provided suggestions to improve the tagging technique. Suggestions included tagging fish that are > 400 mm FL, moving the incision location to extend the cavity and create a pocket for the placement of the SPT, and performing a quantitative wound-healing evaluation. Future studies are therefore recommended to evaluate these suggestions.

59 BASIC BIOLOGICAL SCIENCES↗

PyPVRPM: Photovoltaic Reliability and Performance Model in Python

The ability to perform accurate techno-economic analysis of solar photovoltaic (PV) systems is essential for bankability and investment purposes. Most energy yield models assume an almost flawless operation (i.e., no failures); however, realistically, components fail and get repaired stochastically. This package, PyPVRPM, is a Python translation and improvement of the Language Kit (LK) based PhotoVoltaic Reliability Performance Model (PVRPM), which was first developed at Sandia National Laboratories in Goldsim software (Granata et al., 2011) (Miller et al., 2012). PyPVRPM allows the user to define a PV system at a specific location and incorporate failure, repair, and detection rates and distributions to calculate energy yield and other financial metrics such as the levelized cost of energy and net present value (Klise, Lavrova, et al., 2017). Our package is a simulation tool that uses NREL’s Python interface for System Advisor Model (SAM) (National Renewable Energy Laboratory, 2020b) (National Renewable Energy Laboratory, 2020a) to evaluate the performance of a PV plant throughout its lifetime by considering component reliability metrics. Besides the numerous benefits from migrating to Python (e.g., speed, libraries, batch analyses), it also expands on the failure and repair processes from the LK version by including the ability to vary monitoring strategies. These failures, repairs, and monitoring processes are based on user-defined distributions and values, enabling a more accurate and realistic representation of cost and availability throughout a PV system’s lifetime.

97 MATHEMATICS AND COMPUTING↗