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DOE OSTI2014

NREL RSF Weather Data 2011

Modern buildings are complex energy systems that must be controlled for energy efficiency. The Research Support Facility (RSF) at the National Renewable Energy Laboratory (NREL) has hundreds of controllers -- computers that communicate with the building's various control systems -- to control the building based on tens of thousands of variables and sensor points. These control strategies were designed for the RSF's systems to efficiently support research activities. Many events that affect energy use cannot be reliably predicted, but certain decisions (such as control strategies) must be made ahead of time. NREL researchers modeled the RSF systems to predict how they might perform. They then monitor these systems to understand how they are actually performing and reacting to the dynamic conditions of weather, occupancy, and maintenance. This submission includes the Weather data form the RSF systems energy model. The weather data was used to contextualize and compare energy use data like heating and cooling. The weather data was also used by the RSF Energy Model to model the energy use of the RSF. Energy Model data and Measured Energy data related to the RSF Systems Model can be found in the "Related Datasets" section of this submission.

2011↗

DOE OSTI2014

NREL RSF Measured Data 2011

Modern buildings are complex energy systems that must be controlled for energy efficiency. The Research Support Facility (RSF) at the National Renewable Energy Laboratory (NREL) has hundreds of controllers -- computers that communicate with the building's various control systems -- to control the building based on tens of thousands of variables and sensor points. These control strategies were designed for the RSF's systems to efficiently support research activities. Many events that affect energy use cannot be reliably predicted, but certain decisions (such as control strategies) must be made ahead of time. NREL researchers modeled the RSF systems to predict how they might perform. They then monitor these systems to understand how they are actually performing and reacting to the dynamic conditions of weather, occupancy, and maintenance. This submission includes the Measured Energy Data from the RSF Systems Model. The data includes a csv with measured data from NREL's Research and Support Facility (RSF) for 2011. The dataset contains hourly data for: Total Cooling (kW)- Total Heating (kW)- Total Mechanical (kW)- Total Lighting (kW)- Total Plug Loads (kW)- Total Data Center (kW)- Total Building (kW)- PV (kW)- Building Net (kW). Energy Model data and Weather data related to the RSF Systems Model can be found in the "Related Datasets" section of this submission.

2011↗

DOE OSTI2014

NREL RSF Energy Model 2011

Modern buildings are complex energy systems that must be controlled for energy efficiency. The Research Support Facility (RSF) at the National Renewable Energy Laboratory (NREL) has hundreds of controllers -- computers that communicate with the building's various control systems -- to control the building based on tens of thousands of variables and sensor points. These control strategies were designed for the RSF's systems to efficiently support research activities. Many events that affect energy use cannot be reliably predicted, but certain decisions (such as control strategies) must be made ahead of time. NREL researchers modeled the RSF systems to predict how they might perform. They then monitor these systems to understand how they are actually performing and reacting to the dynamic conditions of weather, occupancy, and maintenance. This submission includes the Energy Model from the RSF Systems Model. Comparing actual performance (metered) with expected performance (modeled) is key to understand corrective actions to ensure performance as originally intended. The Energy Model in this submission was made to model energy usage in the RSF and was compared to actual metered data to verify the model. Measured data and Weather data related to the RSF Systems Model can be found in the "Related Datasets" section of this submission.

2011↗

DOE OSTI2015

SU-E-P-37: Helical Tomotherapy to LINAC Plan Conversion Utilizing RayStation Fallback Planning

Purpose: RayStation Fallback (RSF) plan was developed to switch patient’s treatment from Helical Tomotherapy (HT) to Varian TrueBeam. Helical Tomotherapy plans were compared with the corresponding RSF plans by looking at the following dosimetric parameters: PTV coverage (Dmean and D95), Paddick conformity index (CI), uniformity index (UI=(D98-D2)/Drx) and organ-at-risk (OAR) doses. Methods: Five patients with five tumor sites including larynx, head and neck, esophagus, lung, and prostate previously treated with HT were re-planned using RSF treatment planning station(TPS) to best match the HT treatment plans. IMRT technique with nine fields 6 MV X-ray beams and a static multi-leaf collimator (MLC) were used for RSF plans without any additional attempt to further optimize the RSF plans. Results: A physician evaluated and confirmed the clinical acceptability of the RSF plans. Both HT and RSF plans gave comparable PTV coverage with a maximum percentage difference for D95 of 0.7%. HT plans had a better CIs ranging from 2%–15% higher conformity compared to RSF plans. HT plans also had better UIs for all tumor sites except the esophagus. The UIs were 1.6% to 8.9% lower for HT plans compared to RSF plans. Both HT and RSF plans gave comparable and acceptable OAR doses. However, the integral dose was 1%–15% higher for HT plans compared to RSF plans. Conclusion: RSF plans were simple and fast to generate. In the study cases of 5 various tumor sites, RSF efficiently created clinically acceptable plans without further optimization. However, further optimization for any IMRT plan can be done if clinically warranted. The absolute differences in CI and UI were small between RSF and HT plans.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Recent galaxy mergers and residual star formation of red sequence galaxies in galaxy clusters

This study explored the Galaxy Evolution Explorer ultraviolet (UV) properties of optical red sequence galaxies in four rich Abell clusters at z⩽0.1. In particular, we tried to find a hint of merger-induced recent star formation (RSF) in red sequence galaxies. Using the NUV − r{sup ′} colors of the galaxies, RSF fractions were derived based on various criteria for post-merger galaxies and normal galaxies. Following k-correction, about 36% of the post-merger galaxies were classified as RSF galaxies with a conservative criterion (NUV − r{sup ′}⩽5), and that number was doubled (∼72%) when using a generous criterion (NUV − r{sup ′}⩽5.4). The trend was the same when we restricted the sample to galaxies within 0.5 × R {sub 200}. Post-merger galaxies with strong UV emission showed more violent, asymmetric features in the deep optical images. The RSF fractions did not show any trend along the clustocentric distance within R {sub 200}. We performed a Dressler–Shectman test to check whether the RSF galaxies had any correlation with the substructures in the galaxy clusters. Within R {sub 200} of each cluster, the RSF galaxies did not appear to be preferentially related to the clusters’ substructures. Our results suggested that only 30% of RSF red sequence galaxies show morphological hints of recent galaxy mergers. This implies that internal processes (e.g., stellar mass loss or hot gas cooling) for the supply of cold gas to early-type galaxies may play a significant role in the residual star formation of early-type galaxies at a recent epoch.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Velocity Dependence of Rate‐And‐State Friction in Granular Fault Gouge and Implications for Slow‐Slip Events

Abstract The standard rate‐and‐state friction (RSF) has extensively captured frictional behaviors, but it fails to explain the velocity dependence of frictional stability transition and widespread slow‐slip events (SSEs) in experiments and nature adequately. An alternative microphysical Chen‐Niemeijer‐Spiers (CNS) model can well describe the velocity dependence of frictional behaviors of granular gouges. Using the original CNS model, standard RSF parameters can be quantified microphysically. However, some micro‐parameters are not easy to estimate quantitatively, making it difficult to extrapolate to natural and experimental conditions. Here, we simplify the microphysically‐derived RSF parameters including direct effect a , evolution effect b , and critical slip distance D c , as well as equivalent values ( a eq , b eq , and D eq ). The simplified friction parameters directly illustrate their velocity dependence, namely the essentially constant a , a eq , and D c , negatively velocity‐dependent b and b eq , as well as varying D eq for different laws. They are roughly consistent with experimental results in various fault gouges. A modified CNS model is further derived from the original CNS model, establishing a direct link between the standard RSF and CNS models. The modified CNS model exhibits virtually identical frictional behaviors to the original CNS, but differs from the standard RSF at large velocity perturbations. Moreover, the linearized stability analysis indicates that the critical stiffness for the modified CNS model is velocity‐dependent. Compared with the standard RSF, the modified CNS model not only explains the velocity dependence of frictional stability transition, but also exhibits a more gradual transition for SSEs with a broader range of stiffness ratios.

Geochemistry & Geophysics↗

DOE OSTI2024

Physics informed neural network can retrieve rate and state friction parameters from acoustic monitoring of laboratory stick-slip experiments

Various machine learning (ML) and deep learning (DL) techniques have been recently applied to the forecasting of laboratory earthquakes from friction experiments. The magnitude and timing of shear failures in stick-slip cycles are predicted using features extracted from the recorded ultrasonic or acoustic emission (AE) signals. In addition, the Rate and State Friction (RSF) constitutive laws are extensively used to model the frictional behavior of faults. In this work, we use data from shear experiments coupled with passive acoustic (variance, kurtosis, and AE rate) interleaved with active source ultrasonic monitoring (transmitted wave amplitude) to develop physics-informed neural network (PINN) models incorporating the RSF law and AE rate generation equation with wave amplitude serving as a proxy for friction state variable. This PINN framework allows learning RSF parameters from stick-slip experiments rather than measuring them through a series of velocity step experiments. We observe that when the stick-slip cycles are irregular, the PINN models outperform the data-driven DL models. Transfer learning (TL) PINN models are also developed by pre-training on data collected at one normal stress level followed by forecasting shear failures and retrieving RSF parameters at other stress levels (i.e., with different recurrence intervals) after retraining on a limited amount of new data. Our findings suggest that TL models perform better compared to standalone models. Both standalone and TL PINN-estimated RSF parameters and their ground truth values show excellent agreements thus demonstrating that RSF parameters can be retrieved from laboratory stick-slip experiments using the corresponding acoustic data and that the transmitted wave amplitude provides a good representation of the evolving frictional state during stick-slips.

58 GEOSCIENCES↗

DOE OSTI2022

Improved quantitation of SIMS depth profile measurements of niobium via sample holder design improvements and characterization of grain orientation effects

The importance of SIMS analyses for “N-doped” impurity alloyed niobium and other surface-alloyed materials continues to increase. A major hurdle is the uncertainty of instrument calibration due to changes in sample height either from sample surface topography or from the sample holder itself. The CAMECA sample holder design allows for many types of samples to be analyzed. However, a drawback is that the holder faceplate can bend, contributing an uncertainty in the relative sensitivity factor (RSF) used to quantify the SIMS results. Here, we describe an improved sample holder having a reinforced faceplate, which prevents deflection and reduces uncertainty. Simulations show that the new design significantly reduces deflection from 10 μm to 5 nm. Sample measurements show a reduction of RSF uncertainty from this source from 4.1% to 0.95%. Grain orientation has long been suspected to affect RSF measurement as well. A bicrystal implant standard, consisting of randomly oriented and [001] grains, was successively rotated 15° between analyses. It was observed that 20% of the analyses performed on the randomly oriented grain exhibited anomalously high RSF values as well as slow sputter rates. These features were associated with the changing grain normal orientation with respect to the primary Cs + beam. The grain orientation associated with the rise in RSF was simulated and determined to be the [101] crystallographic plane, thus indicating that ion channeling was responsible for the significantly increased RSF. Focused ion beam analysis confirmed slower sputter rates for the cardinal crystallographic orientations, indicating that ion channeling occurred for each.

43 PARTICLE ACCELERATORS↗

DOE OSTI2017

Sensitivity of Induced Seismic Sequences to Rate-and-State Frictional Processes

It is well established that subsurface injection of fluids increases pore fluid pressures that may lead to shear failure along a preexisting fault surface. Concern among oil and gas, geothermal, and carbon storage operators has risen dramatically over the past decade due to the increase in the number and magnitude of induced earthquakes. Efforts to mitigate the risk associated with injection-induced earthquakes include modeling of the interaction between fluids and earthquake faults. Here we investigate this relationship with simulations that couple a geomechanical reservoir model and RSQSim, a physics-based earthquake simulator. RSQSim employs rate- and state-dependent friction (RSF) that enables the investigation of the time-dependent nature of earthquake sequences. We explore the effect of two RSF parameters and normal stress on the spatiotemporal characteristics of injection-induced seismicity. We perform >200 simulations to systematically investigate the effect of these model components on the evolution of induced seismicity sequences and compare the spatiotemporal characteristics of our synthetic catalogs to observations of induced earthquakes. We find that the RSF parameters control the ability of seismicity to migrate away from the injection well, the total number and maximum magnitude of induced events. Additionally, the RSF parameters control the occurrence/absence of premonitory events. Finally, we find that earthquake stress drops can be modulated by the normal stress and/or the RSF parameters. Insight gained from this study can aid in further development of models that address best practice protocols for injection operations, site-specific models of injection-induced earthquakes, and probabilistic hazard and risk assessments.

58 GEOSCIENCES↗

DOE OSTI2022

Preparation of Highly Crystalline Silk Nanofibrils and Their Use in the Improvement of the Mechanical Properties of Silk Films

Due to their commendable biocompatibility, regenerated silk fibroin (RSF) films have attracted considerable research interest. However, the poor mechanical properties of RSF films have limited their use in various biomedical applications. In this study, a novel, highly crystalline silk fibril was successfully extracted from silk by combining degumming with ultrasonication. Ultrasonication accelerated the development of silk nanofibrils measuring 130–200 nm on the surface of the over-degummed silk fibers, which was confirmed via scanning electron microscopy. Additionally, the crystallinity index of silk fibril was found to be significantly higher (~68%) than that of conventionally degummed silk (~54%), as confirmed by the Fourier-transform infrared (FTIR) spectroscopy results. Furthermore, the breaking strength and elongation of the RSF film were increased 1.6 fold and 3.4 fold, respectively, following the addition of 15% silk nanofibrils. Thus, the mechanical properties of the RSF film were remarkably improved by the addition of the silk nanofibrils, implying that it can be used as an excellent reinforcing material for RSF films.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Solving the sample size problem for resource selection functions

Abstract Sample size sufficiency is a critical consideration for estimating resource selection functions (RSFs) from GPS‐based animal telemetry. Cited thresholds for sufficiency include a number of captured animals and as many relocations per animal N as possible. These thresholds render many RSF‐based studies misleading if large sample sizes were truly insufficient, or unpublishable if small sample sizes were sufficient but failed to meet reviewer expectations. We provide the first comprehensive solution for RSF sample size by deriving closed‐form mathematical expressions for the number of animals M and the number of relocations per animal N required for model outputs to a given degree of precision. The sample sizes needed depend on just 3 biologically meaningful quantities: habitat selection strength, variation in individual selection and a novel measure of landscape complexity, which we define rigorously. The mathematical expressions are calculable for any environmental dataset at any spatial scale and are applicable to any study involving resource selection (including sessile organisms). We validate our analytical solutions using globally relevant empirical data including 5,678,623 GPS locations from 511 animals from 10 species (omnivores, carnivores and herbivores living in boreal, temperate and tropical forests, montane woodlands, swamps and Arctic tundra). Our analytic expressions show that the required M and N must decline with increasing selection strength and increasing landscape complexity, and this decline is insensitive to the definition of availability used in the analysis. Our results demonstrate that the most biologically relevant effects on the utilization distribution (i.e. those landscape conditions with the greatest absolute magnitude of resource selection) can often be estimated with much fewer than animals. We identify several critical steps in implementing these equations, including (a) a priori selection of expected model coefficients and (b) regular sampling of background (pseudoabsence) data within a given definition of availability. We discuss possible methods to identify a priori expectations for habitat selection coefficients, effects of scale on RSF estimation and caveats for rare species applications. We argue that these equations should be a mandatory component for all future RSF studies.

Street, Garrett M.↗

DOE OSTI2023

Comparing Individualized Survival Predictions From Random Survival Forests and Multistate Models in the Presence of Missing Data: A Case Study of Patients With Oropharyngeal Cancer

Background: In recent years, interest in prognostic calculators for predicting patient health outcomes has grown with the popularity of personalized medicine. These calculators, which can inform treatment decisions, employ many different methods, each of which has advantages and disadvantages. Methods: We present a comparison of a multistate model (MSM) and a random survival forest (RSF) through a case study of prognostic predictions for patients with oropharyngeal squamous cell carcinoma. The MSM is highly structured and takes into account some aspects of the clinical context and knowledge about oropharyngeal cancer, while the RSF can be thought of as a black-box non-parametric approach. Key in this comparison are the high rate of missing values within these data and the different approaches used by the MSM and RSF to handle missingness. Results: We compare the accuracy (discrimination and calibration) of survival probabilities predicted by both approaches and use simulation studies to better understand how predictive accuracy is influenced by the approach to (1) handling missing data and (2) modeling structural/disease progression information present in the data. We conclude that both approaches have similar predictive accuracy, with a slight advantage going to the MSM. Conclusions: Although the MSM shows slightly better predictive ability than the RSF, consideration of other differences are key when selecting the best approach for addressing a specific research question. These key differences include the methods’ ability to incorporate domain knowledge, and their ability to handle missing data as well as their interpretability, and ease of implementation. Ultimately, selecting the statistical method that has the most potential to aid in clinical decisions requires thoughtful consideration of the specific goals.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

ECAR-6584 MARVEL Reactor Support Frame Analysis

Idaho National Laboratory (INL) is developing a small microreactor to produce electrical power utilizing a small nuclear core and Stirling engines for power output under the Microreactor Application Research Validation and Evaluation (MARVEL) program. The MARVEL Reactor will be installed in the Transient Reactor Test (TREAT) Facility. Walsh Engineering Services, PC (WES) has contracted with the INL to support the completion of the final design. There are six main systems in the MARVEL, one of which is the MARVEL Reactor System (MRS). The MRS contains a subsystem – the Reactor Support Frame (RSF) – that supports and orients nearly all the MRS and the RSF will be bolted to the TREAT Facility. The subject of this Engineering Calculations and Analysis Report (ECAR) is the frame weldment (see Figure 1), which is the only item that is contained in the RSF subsystem and will be called herein “RSF”.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2013

Metering Best Practices Applied in the National Renewable Energy Laboratory's Research Support Facility: A Primer to the 2011 Measured and Modeled Energy Consumption Datasets

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

Metering Best Practices Applied in the National Renewable Energy Laboratory's Research Support Facility: A Primer to the 2011 Measured and Modeled Energy Consumption Datasets

47 OTHER INSTRUMENTATION↗

DOE OSTI2016

Metering Best Practices Applied in the National Renewable Energy Laboratory's Research Support Facility: A Primer to the 2011 Measured and Modeled Energy Consumption Datasets

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

The Impact of Frictional Healing on Stick-Slip Recurrence Interval and Stress Drop: Implications for Earthquake Scaling: The impact of healing on stick-slip

We report that interseismic frictional healing is an essential process in the seismic cycle. Observations of both natural and laboratory earthquakes demonstrate that the magnitude of stress drop scales with the logarithm of recurrence time, which is a cornerstone of the rate and state friction (RSF) laws. However, the origin of this log linear behavior and short time “cutoff” for small recurrence intervals remains poorly understood. Here we use RSF laws to demonstrate that the back-projected time of null-healing intrinsically scales with the initial frictional state θ i . We explore this behavior and its implications for (1) the short-term cutoff time of frictional healing and (2) the connection between healing rates derived from stick-slip sliding versus slide-hold-slide tests. We use a novel, continuous solution of RSF for a one-dimensional spring-slider system with inertia. The numerical solution continuously traces frictional state evolution (and healing) and shows that stick-slip cutoff time also scales with frictional state at the conclusion of the dynamic slip process θ i (=D c /V peak ). This numerical investigation on the origins of stick-slip response is verified by comparing laboratory data for a range of peak slip velocities. Slower slip motions yield lesser magnitude of friction drop at a given time due to higher frictional state at the end of each slip event. In conclusion, our results provide insight on the origin of log linear stick-slip evolution and suggest an approach to estimating the critical slip distance on faults that exhibit gradual accelerations, such as for slow earthquakes.

58 GEOSCIENCES↗

DOE OSTI2024

The Effect of Normal Stress Oscillations on Fault Slip Behavior Near the Stability Transition From Stable to Unstable Motion

Tectonic fault zones are subject to normal stress variations with a wide range of spatio-temporal scales. Stress perturbations cover a wide range of frequencies and amplitudes from high frequency seismic waves generated by earthquakes to low frequency transients associated with solid Earth tides. These perturbations can reactivate critically stressed faults and trigger earthquakes. Here, we describe lab experiments to illuminate the physics of such changes in friction and the mechanics of earthquake triggering and fault reactivation. Friction tests were done in a double direct shear configuration for conditions near the stability transition from stable to unstable motion. We studied simulated fault gouge composed of quartz powder and conducted experiments at reference normal stress from 10 to 13.5 MPa. After shearing to steady state sliding, we applied sinusoidal normal stress oscillations of amplitude 0.5–2 MPa, and period of 0.5–50 s. We performed numerical simulations using measured values of rate and state friction (RSF) parameters to assess our data. Our results show that low frequency stress oscillations cause a Coulomb-like response of shear strength that transitions from stable slip to slow lab earthquakes as frequency increases. At the critical frequency predicted by RSF we observe periodic stick-slip behavior. Perturbations of high amplitude and short period weaken the fault, while lower amplitudes strengthen the fault. We find that a modified RSF formulation is able to accurately match our laboratory data. Our findings highlight the complex effects of stress perturbations on fault strength and the mode of fault slip.

58 GEOSCIENCES↗