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At least 487 records · Page 27

PALMO: An OVERFLOW Machine Learning Airfoil Performance Database

The OVERFLOW Machine Learning Airfoil Performance (PALMO) database has been created to enable robust modeling of airfoil performance in a variety of applications. The PALMO database uses OVERFLOW simulation data second-order accurate in time and fourth-order accurate in space with Spalart-Allmaras turbulence closure. The foundation of the in-development PALMO database is the airfoil base cube. Each base cube includes simulation data parametrized over a range of Mach numbers, Reynolds numbers, and angles-of-attack. This database includes the NACA 4-series airfoils, with parametrization in airfoil thickness and camber from an NACA 0006 to an NACA 4424. In total, 52,480 NACA 4-series OVERFLOW calculations were run on the NASA High-End Compute Capability (HECC) supercomputer. This provides high-order-accurate simulation data covering a wide range of aerospace design applications, which enables users to develop accurate airfoil performance look-up tables without additional high-performance computing. In addition to engineering design and analysis of aerospace vehicles, PALMO is well suited to be a benchmark dataset for the development and testing of machine learning methods in aerospace engineering. This work presents an example PALMO surrogate model that enables accurate airfoil performance predictions for any arbitrary combination of camber, thickness, Mach number, Reynolds number, and angle of attack within the bounds of the database. Airfoil performance tables predicted for an airfoil not used in training the model are used in three-dimensional OVERFLOW simulations to quantify the downstream accuracy on aggregate rotor performance metrics. For the NACA 3415 airfoil, which had no common thickness or camber with the training data, the surrogate predicted and CFD generated tables were within 2.1% of each other in the forward flight lift to drag metric. This suggests that performance tables generated for airfoils within the bounds of the PALMO database will yield aggregate rotor performance predictions on par with tables generated from directly running OVERFLOW airfoil calculations. The PALMO airfoil performance coefficients are available publicly.

Database↗

Design and implementation of I/O performance prediction scheme on HPC systems through large-scale log analysis

Abstract Large-scale high performance computing (HPC) systems typically consist of many thousands of CPUs and storage units used by hundreds to thousands of users simultaneously. Applications from large numbers of users have diverse characteristics, such as varying computation, communication, memory, and I/O intensity. A good understanding of the performance characteristics of each user application is important for job scheduling and resource provisioning. Among these performance characteristics, I/O performance is becoming increasingly important as data sizes rapidly increase and large-scale applications, such as simulation and model training, are widely adopted. However, predicting I/O performance is difficult because I/O systems are shared among all users and involve many layers of software and hardware stack, including the application, network interconnect, operating system, file system, and storage devices. Furthermore, updates to these layers and changes in system management policy can significantly alter the I/O behavior of applications and the entire system. To improve the prediction of the I/O performance on HPC systems, we propose integrating information from several different system logs and developing a regression-based approach to predict the I/O performance. Our proposed scheme can dynamically select the most relevant features from the log entries using various feature selection algorithms and scoring functions, and can automatically select the regression algorithm with the best accuracy for the prediction task. The evaluation results show that our proposed scheme can predict the write performance with up to 90% prediction accuracy and the read performance with up to 99% prediction accuracy using the real logs from the Cori supercomputer system at NERSC.

97 MATHEMATICS AND COMPUTING↗

Paving the Way for Net Zero Energy Codes through Performance Based Approaches

The prescriptive path is the most widely used approach for commercial code compliance in the United States. However, to achieve near-term net zero energy performance that many stakeholders in the buildings industry desire, it is clear that energy codes will need to transition from prescriptive to performance-based approaches. However, that transition is not without potential pitfalls. Among the concerns expressed by stakeholders are added complexity and cost, lack of confidence in energy modeling results, gamesmanship on the part of applicants, lack or qualified reviewers, challenges in promoting de-carbonization, and the inequity of trading long lived envelope efficiency for short lived measures such as building controls. This paper will discuss multiple approaches being evaluated and implemented by Pacific Northwest National Laboratory to improve the usability of the performance-based approach for both code compliance and beyond code programs to meet aggressive energy savings targets. A 'system performance' approach provides a simpler approach compared to whole building performance, while keeping tradeoffs limited to specific building systems. A simplified whole-building performance-based approach for small commercial buildings can cost effectively achieve deeper savings for buildings that typically follow the prescriptive compliance approach. Improved reporting and verification processes applied to the traditional performance path can provide greater confidence in simulation results and facilitate adoption of performance-based approaches. Prescriptive packages provide prescriptive solutions while targeting specific performance thresholds. This paper discusses the progress being made with each of these approaches and provides examples of their implementation in energy codes and beyond code programs.

Performance Based Codes, Appendix G, PRM, TSPR, Sy↗

Performance of cross-flow turbines with varying blade materials and unsupported blade span

Cross-flow turbines could play a larger role in the diversification of the global energy supply if the impact of more cost-competitive design choices on performance and rotor dynamics was better understood. This study focuses on rotor performance and blade strain measurements while varying the following parameters: blade materials and blade free end length by changing strut support position. Towing tank experiments were performed with a modular 1-meter diameter cross-flow turbine consisting of three NACA 0018 blades with two support struts. One strut was fixed at the lower end of the turbine, while the second strut was adjustable, thereby changing the length of the free end. The blade materials tested were carbon, E-glass, and hollow E-glass fiber composites, in decreasing order of stiffness and cost. High-resolution distributed fiber optic sensors were embedded in two of the three rotor blades for each material and provided hundreds of strain measurements per blade. Turbine performance and blade strain were measured while varying tow speed and tip speed ratio. Performance tests were conducted at towing speeds sufficiently high for the performance to be independent of Reynolds number. E-glass blades and carbon blades performed similarly for the most rigid strut configurations. Higher strain was measured on the E-glass blades, and their performance was reduced for less rigid configurations compared to the carbon fiber blades. The performance of the highly deflective hollow E-glass blades was lower overall and became even more degraded for longer unsupported blade span. Furthermore, the results provide insight into the use of various blade materials in cross-flow turbines and guidance on allowable free end length for each material type.

16 TIDAL AND WAVE POWER↗

Design and Manufacturing of High Performance, Reduced Charge Heat Exchangers

Air-to-fluid heat exchangers (HXs) play a critical role as the main heat transfer component in Heating, Ventilation, Air-Conditioning, and Refrigeration (HVAC&R) systems. However, their airside thermal resistance significantly inhibits their overall performance. Furthermore, these HXs must be continually more compact to meet the latest refrigerant charge limits to reduce emissions. Recent literature suggests that traditional HX geometries (e.g., round or flat tubes with fins), have reached their limits, and more sophisticated shape- and topology-optimized designs are required to achieve the next jump in performance. This research sheds light on the next generation of air-to-refrigerant HXs and aims to address several practical issues to commercialization such as novelty challenges (improved performance for significant charge reduction; modeling expertise & time investment), manufacturing challenges (non-round tube manufacturing; tube-header integration; product qualification, e.g., burst pressure testing, extreme operational environment, etc.), and operational challenges (flow maldistribution, fouling & wetting, noise & vibration). For example, a >20% improvement on one (or more) HX-level performance metrics (e.g., envelope volume, airside pressure drop, face area, capacity, refrigerant charge, weight, cost, etc.) must be achieved before a HX design is considered for commercialization. We present a new, comprehensive and experimentally validated air-to-refrigerant HX optimization framework with simultaneous thermal-hydraulic performance and mechanical strength considerations for novel, non-round, shape- and topology-optimized tubes capable of optimizing single and two-phase HX designs for any refrigerant choice and performance requirement with significant engineering time savings compared to conventional design practices. The framework was exercised for a wide range of applications and refrigerants, resulting in HXs which achieved greater than 20% improved performance, 20% reductions in size, and 25% reductions in refrigerant charge. To enable non-round tube bundle use in next generation HVAC&R equipment, novel manufacturing techniques were investigated, including the development of conventional manufacturing methods for small diameter, non-round tubes and novel tube-header integration strategies. In total, ten HX prototypes were manufactured, nine using conventional methods directly attributed to this project and one using advanced additive manufacturing methods. The five-year manufacturing feasibility of the proposed HXs was found to have a good outlook. The non-round tube HX simulated performance was validated through comprehensive experimental testing, including nine in-house component-level tests, one independent component-level test at an industry partner laboratory, and in-house system-level tests of using a commercially-available, residential packaged A/C unit which was retrofitted with a non-round tube prototype HX. It was found that HX designs proposed by the new framework can successfully predict experimental thermal-hydraulic performance within ±10-20% the first time with no manual design changes, eliminating the need for time-consuming and expensive prototyping efforts. This work will accelerate design and time to market for next generation HXs while simultaneously facilitating industry transition to new refrigerants at lower charge.

42 ENGINEERING↗

Evaluating Alerting and Guidance Performance of a UAS Detect-And-Avoid System

A key challenge to the routine, safe operation of unmanned aircraft systems (UAS) is the development of detect-and-avoid (DAA) systems to aid the UAS pilot in remaining "well clear" of nearby aircraft. The goal of this study is to investigate the effect of alerting criteria and pilot response delay on the safety and performance of UAS DAA systems in the context of routine civil UAS operations in the National Airspace System (NAS). A NAS-wide fast-time simulation study was conducted to assess UAS DAA system performance with a large number of encounters and a broad set of DAA alerting and guidance system parameters. Three attributes of the DAA system were controlled as independent variables in the study to conduct trade-off analyses: UAS trajectory prediction method (dead-reckoning vs. intent-based), alerting time threshold (related to predicted time to LoWC), and alerting distance threshold (related to predicted Horizontal Miss Distance, or HMD). A set of metrics, such as the percentage of true positive, false positive, and missed alerts, based on signal detection theory and analysis methods utilizing the Receiver Operating Characteristic (ROC) curves were proposed to evaluate the safety and performance of DAA alerting and guidance systems and aid development of DAA system performance standards. The effect of pilot response delay on the performance of DAA systems was evaluated using a DAA alerting and guidance model and a pilot model developed to support this study. A total of 18 fast-time simulations were conducted with nine different DAA alerting threshold settings and two different trajectory prediction methods, using recorded radar traffic from current Visual Flight Rules (VFR) operations, and supplemented with DAA-equipped UAS traffic based on mission profiles modeling future UAS operations. Results indicate DAA alerting distance threshold has a greater effect on DAA system performance than DAA alerting time threshold or ownship trajectory prediction method. Further analysis on the alert lead time (time in advance of predicted loss of well clear at which a DAA alert is first issued) indicated a strong positive correlation between alert lead time and DAA system performance (i.e. the ability of the UAS pilot to maneuver the unmanned aircraft to remain well clear). While bigger distance thresholds had beneficial effects on alert lead time and missed alert rate, it also generated a higher rate of false alerts. In the design and development of DAA alerting and guidance systems, therefore, the positive and negative effects of false alerts and missed alerts should be carefully considered to achieve acceptable alerting system performance by balancing false and missed alerts. The results and methodology presented in this study are expected to help stakeholders, policymakers and standards committees define the appropriate setting of DAA system parameter thresholds for UAS that ensure safety while minimizing operational impacts to the NAS and equipage requirements for its users before DAA operational performance standards can be finalized.

UAS Detect-and-Avoid (DAA) System↗

2023 Artemis Crew Health and Performance System Model Development

While the NASA Human Research Program (HRP) utilizes a Crew Health and Performance (CHP) System to represent all the Agency’s efforts to ensure the health and performance of NASA astronauts, there is no shared mental model of a CHP system at NASA. Some groups may consider a CHP system to be only a medical kit, while others may not be using the concept at all. To facilitate the integration of functions and capabilities to ensure astronaut health and performance during vehicle development, HRP has proposed a CHP Shared Mental Model derived from the NASA Human Health, Medical, and Performance Spaceflight Standards (NASA-STD-3001 Vol.1/Vol.2). [1] Even though many vehicle, ground, and communication systems as well as mission operations are modeled for the Artemis Campaigns, no mission level CHP system model was created to achieve the intent of the HRP CHP Shared Mental Model. The lack of this model renders it difficult to visualize and understand how the many programs work together to provide the necessary cross program functions and capabilities to ensure the health and performance of the crew throughout an Artemis mission. For this purpose, the Exploration Medical Capability (ExMC) element of HRP developed a CHP system model for the Artemis III and IV missions to provide a view of how each program contributes to and interacts with the overall CHP system. To develop the 2023 Artemis CHP system model, ExMC leveraged existing data and models from the Moon to Mars Program Office, the Office of the Chief Health and Medical Officer (OCHMO) and the Orion, Gateway, Extravehicular Activity and Human Surface Mobility (EHP) and Human Landing System (HLS) programs. By using a Model-Based Systems Engineering (MBSE) approach, existing requirements, functions, and concepts of operations were combined to create a single system model focused on representing CHP from the launch to the return to Earth segments of the Artemis III and IV missions. Additionally, by incorporating the HRP Systems Platform for Aggregating and Relating Capabilities, or SPARC tool, the data from the programs was also related back to the 2nd volume of the NASA Human Health, Medical, and Performance Spaceflight Standard (NASA-STD-3001, Vol.2) and the human system risks identified by the Human System Risk Board (HSRB). The first version of the 2023 Artemis CHP system model was baselined in Fall of 2023 after the model was demonstrated to be a potentially useful tool for systems engineers integrating CHP capabilities in vehicle development as well as members of the Health and Medical Technical Authority providing oversight of those programs. The model may also be useful to any stakeholder of astronaut health and performance by providing insights on how an Artemis mission satisfies the NASA Human Health, Medical, and Performance Spaceflight Standards as well as how they mitigate the HSRB Human System Risks. This presentation highlights how the model was developed and the possible benefits of the model. [1] NASA HRP (2022), Crew Health and Performance System Whitepaper

Systems engineering↗

2023 Artemis Crew Health and Performance (CHP) System Model Development

While the NASA Human Research Program (HRP) utilizes a Crew Health and Performance (CHP) System to represent all the Agency’s efforts to ensure the health and performance of NASA astronauts, there is no shared mental model of a CHP system at NASA. Some groups may consider a CHP system to be only a medical kit, while others may not be using the concept at all. To facilitate the integration of functions and capabilities to ensure astronaut health and performance during vehicle development, HRP has proposed a CHP Shared Mental Model derived from the NASA Human Health, Medical, and Performance Spaceflight Standards (NASA-STD-3001 Vol.1/Vol.2). [1] Even though many vehicle, ground, and communication systems as well as mission operations are modeled for the Artemis Campaigns, no mission level CHP system model was created to achieve the intent of the HRP CHP Shared Mental Model. The lack of this model renders it difficult to visualize and understand how the many programs work together to provide the necessary cross program functions and capabilities to ensure the health and performance of the crew throughout an Artemis mission. For this purpose, the Exploration Medical Capability (ExMC) element of HRP developed a CHP system model for the Artemis III and IV missions to provide a view of how each program contributes to and interacts with the overall CHP system. To develop the 2023 Artemis CHP system model, ExMC leveraged existing data and models from the Moon to Mars Program Office, the Office of the Chief Health and Medical Officer (OCHMO) and the Orion, Gateway, Extravehicular Activity and Human Surface Mobility (EHP) and Human Landing System (HLS) programs. By using a Model-Based Systems Engineering (MBSE) approach, existing requirements, functions, and concepts of operations were combined to create a single system model focused on representing CHP from the launch to the return to Earth segments of the Artemis III and IV missions. Additionally, by incorporating the HRP Systems Platform for Aggregating and Relating Capabilities, or SPARC tool, the data from the programs was also related back to the 2nd volume of the NASA Human Health, Medical, and Performance Spaceflight Standard (NASA-STD-3001, Vol.2) and the human system risks identified by the Human System Risk Board (HSRB). The first version of the 2023 Artemis CHP system model was baselined in Fall of 2023 after the model was demonstrated to be a potentially useful tool for systems engineers integrating CHP capabilities in vehicle development as well as members of the Health and Medical Technical Authority providing oversight of those programs. The model may also be useful to any stakeholder of astronaut health and performance by providing insights on how an Artemis mission satisfies the NASA Human Health, Medical, and Performance Spaceflight Standards as well as how they mitigate the HSRB Human System Risks. This presentation highlights how the model was developed and the possible benefits of the model. [1] NASA HRP (2022), Crew Health and Performance System Whitepaper

Systems engineering↗

Impact of Dry Cooler Air-Side Performance on a sCO2 Power Cycle for a CSP Application

Uncertainty around the design and control of the supercritical CO2 power cycle must be reduced before this technology can be implemented for large-scale grid support. To better understand the day-to-day performance of an sCO2 cycle, off-design performance calculations must be included for all power block components, and performance assumptions must be removed. This study has expanded the modeled scope to include the air-side performance for the dry cooler and has incorporated discretized heat transfer calculations for both streams through the pre-cooler to better predict off-design performance. This study considered a recompression Brayton cycle in a concentrating solar power application. The cycle model utilized fixed sCO2 turbomachinery maps for the main compressor, recompressor, and expander operating to supply approximately 10 MW gross at the design point. Fixed vendor-supplied fan curves were used to calculate the air-side performance of the dry cooler. The primary heater was modeled considering both the sCO2 and heat transfer fluid streams. Off-design performance was predicted for an ambient temperature range of 0-55℃, a HTF temperature range of 705-735℃, and a HTF mass flow range of 50-105% of the design point value. To understand the importance of modeling the air-side performance, the cycle off-design performance was also calculated using a constant CO2 outlet temperature assumption and a constant approach temperature assumption for the dry cooler. Results show that using these assumptions can significantly alter the power output and cycle efficiency predictions.

14 SOLAR ENERGY↗

Performance and transport in the ARC tokamak

The ARC TM tokamak, a high-field (𝐵 𝑇 = 11.4 T) fusion power plant, under development by Commonwealth Fusion Systems, is studied using a suite of integrated modelling tools to predict its fusion power generation (𝑃𝑓⁡𝑢⁢𝑠), transport and confinement properties. Analysis is based off an ARC operational point scoped first with zero-dimensional (0-D) plasma operational contour (POPCON) modelling to produce 1.13 GW of fusion power. A suite of integrated modelling tools (TRANSP, ASTRA and TORAX) were applied to predict the performance and kinetic profiles of the ARC design point, yielding a range of predicted performance spanning from ∼900 to 1300 MW in rough quantitative agreement with POPCON predictions. The sensitivity of these results to uncertain modelling inputs was probed using scans of pedestal boundary conditions around EPED-predicted values (total pressure and temperature ratios), tungsten concentration and seperatrix density around their nominal assumptions. Pedestal pressure and pedestal top (𝑇 𝑖 /𝑇 𝑒 ) play a large role in 1.5-dimensional performance predictions, able to modify the predicted 𝑃 𝑓⁡𝑢⁢𝑠 by a factor of 2 within reasonable assumptions. High-fidelity core nonlinear gyrokinetic profile predictions, performed using CGYRO (Candy et al. 2016 J. Comput. Phys., vol. 324, pp. 73–93) coupled with the PORTALS (Rodriguez-Fernandez et al. 2024 Nucl. Fusion, vol. 64, 076034; Phys. Plasmas, vol. 31, 2024, 062501) framework, yield substantially lower performance (𝑃 𝑓⁡𝑢⁢𝑠 =677 MW) compared with 0-D and medium-fidelity modelling for nominal assumptions, showing that there is non-negligible uncertainty between models and that future work on SPARC may help resolve discrepancies. Lower overall performance results from significantly reduced volume-averaged densities and temperatures, along with reduced levels of density and temperature peaking. Turbulence and transport are largely dominated by ion temperature gradient across the profile, confirmed by both linear stability and the response of the nonlinear fluxes to changes in gradients, with some impact of kinetic ballooning modes in the deep core. This work represents one of the most complete scoping of potential fusion power plant conditions performed to date. The extensive integrated modelling provides confidence in ARC performance approaching 1 GW, while nonlinear gyrokinetic modelling results in open questions into the physics of density and temperature peaking in fusion-power-plant-relevant operational space. A discussion of results and the role that the SPARC tokamak (Creely et al. 2020 J. Plasma Phys., vol. 86, 865860502) will play in informing ARC design, performance and operation is presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Efficient population representation with more genetic markers increases performance of a steelhead (Oncorhynchus mykiss) genetic stock identification baseline

Abstract Genetic stock identification (GSI) is an important fisheries management tool to identify the origin of fish harvested in mixed stock fisheries. Periodic updates of genetic baselines can improve performance via the addition of unsampled or under‐sampled populations and the inclusion of more informative markers. We used a combination of baselines to evaluate how population representation, marker number, and marker type affected the performance and accuracy of genetic stock assignments (self‐assignment, bias, and holdout group tests) for steelhead ( Oncorhynchus mykiss ) in the Snake River basin. First, we compared the performance of an existing genetic baseline with a newly developed one which had a reduced number of individuals from more populations using the same set of markers. Self‐assignment rates were significantly higher ( p < 0.001; +5.4%) for the older, larger baseline, bias did not differ significantly between the two, but there was a significant improvement in performance for the new baseline in holdout results ( p < 0.001; mean increase of 25.0%). Second, we compared the performance of the new baseline with increased numbers of genetic markers (~2x increase of single‐nucleotide polymorphisms; SNPs) for the same set of baseline individuals. In this comparison, results produced significantly higher rates of self‐assignment ( p < 0.001; +9.7%) but neither bias nor leave‐one‐out were significantly affected. Third, we compared 334 SNPs versus opportunistically discovered microhaplotypes from the same amplicons for the new baseline, and showed the latter produced significantly higher rates of self‐assignment ( p < 0.01; +2.6%), similar bias, but slightly lower holdout performance (−0.1%). Combined, we show the performance of genetic baselines can be improved via representative and efficient sampling, that increased marker number consistently improved performance over the original baseline, and that opportunistic discovery of microhaplotypes can lead to small improvements in GSI performance.

Hargrove, John S.↗

HVAC System Performance for Energy Codes (Technical Brief)

The prescriptive path is likely the most widely used approach for commercial code compliance in the United States. Though easy to implement, the prescriptive approach does not discriminate between high-performing and poorly performing heating, ventilation, air conditioning (HVAC) system configurations that are both minimally compliant. To meet aggressive energy and carbon reduction goals, energy codes will need to transition from prescriptive to performance-based approaches, a transition that is riddled with several challenges. HVAC System Performance is a discipline performance path and provides a simpler solution to HVAC system evaluation compared to whole building performance, while keeping tradeoffs limited to specific building systems. The Total System Performance Ratio (TSPR) is a metric for evaluation of overall system efficiency instead of individual component efficiency, a solution that could also eventually facilitate the transition to a 100% performance-based code structure. TSPR is a ratio that compares the annual heating and cooling load of a building to the annual energy consumed by the building’s HVAC system. A web-based calculation tool has been developed for determining a building’s TSPR. Already incorporated into the 2018 Washington State Energy Code, this approach has also been evaluated by the ASHRAE Standard 90.1 Project Committee and has the potential to provide a comprehensive performance-based approach for HVAC system evaluation and analysis

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Benchmark Tracking System for Performance Monitoring

Benchmarking is essential for high-performance software development, particularly for monitoring performance across code iterations. This project focused on enhancing the benchmarking process for Lamellar, an asynchronous runtime for High-Performance Computing (HPC) systems developed at Pacific Northwest National Laboratory. Prior to this work, benchmark results were difficult to track and compare across code versions, presenting significant challenges in identifying performance regressions and long-term trends. The primary objective was to establish a systematic, reproducible approach for measuring performance and detecting regressions following code commits. Our methodology involved three key components: standardizing benchmark outputs, implementing data versioning, and developing analysis tools. We standardized the benchmark output format to JSON Line records containing specific fields (execution time, hardware specifications, and environmental variables). To address data management challenges, we evaluated several options and eventually chose a git repository dedicated to benchmark data. We developed a suite of Python tools that processed benchmark results, enriched them with metadata, and facilitated search in the repository. The resulting system enables more efficient filtering and comparison of performance metrics across commit histories, hardware configurations, and benchmark variants through a unified query interface. Our implementation reduces computational overhead by first checking for existing results through configuration matching before initiating new benchmark runs, thereby conserving resources. The system has been validated by Lamellar developers. It organizes results by benchmark type and build configurations for efficient retrieval. Future developments include a planned Large Language Model interface for predicting benchmark performance, incorporating the criterion package for statistical analysis, which will enable automated detection of statistically significant performance changes, and integration with continuous integration pipelines. Despite these enhancements being reserved for future work, this project has successfully provided the Lamellar development team with a framework for maintaining consistent performance standards and identifying optimization opportunities across workloads and hardware environments.

97 MATHEMATICS AND COMPUTING↗

Methodology to Establish Performance Targets for Building Energy Codes

This report explains the underlying development of the U.S. NZE building sector performance targets reported in Federal Register Notice XX. This document also includes NZE performance targets for U.S. states, which were developed following the same procedures used to develop the national values. These national and state targets are intended to support the establishment and attainment of NZE goals over time. Where residential and commercial building energy code compliance mechanisms apply to new buildings and major renovations and dictate performance requirements, these targets reflect the recommended, minimum levels of performance. Appendix A provides the performance values and targets by U.S. state for residential and commercial buildings. These include each state’s adopted energy code performance, current published MEC performance value, and a nominal NZE code compliance performance target. The current code and NZE values can be compared to the state adopted code value to indicate the level of advancement needed to move towards recommended NZE building performance levels. Additional supplemental resources are available to support states and local governments ready to move from setting NZE policy goals to adopting NZE codes. More information about these resources and the actions states can take to achieve NZE buildings with energy codes are provided in the body of this document.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Filtration Performance of Simulated 200 West Area Waste Feeds

This report describes the scaled experimental system and approach used to examine dead-end filtration performance of representative 200W waste feeds. The scaled system, which was originally designed and assembled to test Tank Side Cesium Removal (TSCR) system performance with higher-than-expected solid loadings in 2021 (Schonewill et al. 2021), was repurposed to conduct the current experiments at ~1/145 of full scale (based on throughput). Six experimental runs were conducted with five different 200W waste feed simulants: three using a DEF module scaled for TSCR and three using a DEF module scaled for the 200W process modules (based on the current design for the Advanced Modular Pretreatment System). Each experiment was run continuously for multiple days with an operating approach prototypic of the full-scale system. Staff performing the experimental runs monitored performance, obtained data from calibrated process instruments, and collected samples for observation and analysis. The measured data are presented with a focus on assessing DEF performance – specifically, the filters’ differential pressure response to the five waste simulants, frequency and efficacy of backwashing, and baseline recovery between experimental runs; data related to ion exchange column performance are also discussed in cases where the opportunity arose. The experimental campaign demonstrated that the DEFs satisfied their primary function of protecting the ion exchange column from solid intrusion for all the representative simulants used. The filters readily handled solids loadings of =500 ppm (and even greater), especially the modules scaled to the 200W process modules. Adjustments to the processing flow rate and reductions in feed temperature were observed to affect the rate of differential pressure increase on the filters, but neither adversely affected the ability of the DEFs to perform their primary function. Backflushing reliably recovered filter performance in all runs, although it did not prevent irreversible fouling for one simulant. The run that exhibited irreversible fouling established that both the quantity and the nature of the solids being filtered need to be considered when projecting filter performance.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks. Funding: AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 ( https://www.nfdi4health.de/task-force-covid-19-2 ) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z).

60 APPLIED LIFE SCIENCES↗

Skylab program earth resources experiment package. Volume 5: Sensor performance evaluation (S193 ALT)

The results are summarized of S193 altimeter sensor performance evaluation based on data presented to the sensor performance evaluation interim reports. The results of additional analyses of S193 altimeter performance are presented, and techniques used in sensor performance evaluation are described. Significant performance degradation identified during the Skylab missions and the performance achieved are described in terms of pertinent S193 altimeter parameters. The additional analyses include final performance analyses completed after submittal of the SL4 interim sensor performance evaluation reports, including completion of detailed analyses of basic performance parameters initiated during the interim report periods.

Kenney, G. P.↗

Performance of a distributed superscalar storage server

The RS/6000 performed well in our test environment. The potential exists for the RS/6000 to act as a departmental server for a small number of users, rather than as a high speed archival server. Multiple UniTree Disk Server's utilizing one UniTree Disk Server's utilizing one UniTree Name Server could be developed that would allow for a cost effective archival system. Our performance tests were clearly limited by the network bandwidth. The performance gathered by the LibUnix testing shows that UniTree is capable of exceeding ethernet speeds on an RS/6000 Model 550. The performance of FTP might be significantly faster if asked to perform across a higher bandwidth network. The UniTree Name Server also showed signs of being a potential bottleneck. UniTree sites that would require a high ratio of file creations and deletions to reads and writes would run into this bottleneck. It is possible to improve the UniTree Name Server performance by bypassing the UniTree LibUnix Library altogether and communicating directly with the UniTree Name Server and optimizing creations. Although testing was performed in a less than ideal environment, hopefully the performance statistics stated in this paper will give end-users a realistic idea as to what performance they can expect in this type of setup.

Finestead, Arlan↗