SEARCH · Search NASA

Results for “Avoidance”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,081 records · Page 60

All sources NASA NTRS DOE OSTI

DOE OSTI2016

TU-FG-201-07: Development of SRS Conical Collimator Collision Prediction Software for Radiation Treatment Safety

Purpose: Stereotactic radiosurgery (SRS) treatments using conical collimators can potentially result in gantry collision with treatment table due to limited collision-clear spaces. An in-house software was developed to help the SRS treatment planner mitigate potential SRS conical collimator (Varian Medical System, Palo Alto, CA) collisions with the treatment table. This software was designed to remove treatment re-planning secondary to unexpected collisions. Methods: A BrainLAB SRS ICT Frameless Extension used for SRS treatments in our clinic was mathematically modelled using surface points registered to the 3D co-ordinate space of the couch extension. The surface points are transformed based on the treatment isocenter point and potential collisions are determined in 3D space for couch and gantry angle combinations. The distance between the SRS conical collimators and LINAC isocenter is known. The collision detection model was programmed in MATLAB (Mathwork, Natick, MA) to display graphical plots of the calculations, and the plotted data is used to avoid the gantry and couch angle combinations that would likely result in a collision. We have utilized the cone collision tool for 23 SRS cone treatment plans (8 retrospective and 15 prospective for 10 patients). Results: Twenty one plans strongly agreed with the software tool prediction for collision. However, in two plans, a collision was observed with a 0.5 cm margin when the software predicted no collision. Therefore, additional margins were added to the clearance criteria in the program to achieve a lower risk of actual collisions. Conclusion: Our in-house developed collision check software successfully avoided SRS cone re-planning by 91.3% due to a reduction in cone collisions with the treatment table. Future developments to our software will include a CT image data set based collision prediction model as well as a beam angle optimization tool to avoid normal critical tissues as well as previously treated lesions.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Impact of Electrolyte Solvent on Li 4 Ti 5 O 12 /LiNi 0.90 Mn 0.05 Co 0.05 O 2 Battery Performance for Behind-the-Meter Storage Applications

Behind-the-Meter Storage (BTMS) systems require dedicated development of battery materials that target long cycle life and low cost at the system level. Pairing Li 4 Ti 5 O 12 (LTO) and LiNi 0.9 Mn 0.05 Co 0.05 O 2 (NMC90-5-5) shows promise to achieve targets for BTMS applications; however, minimal literature is available that discusses electrolyte solvent selection for this pairing. This study explores the role of electrolyte solvent on cycle life in LTO/NMC90-5-5 batteries. Four model electrolytes are evaluated; the baseline, Gen2, is compared with 1M LiPF 6 added to each of three separate solvents: ethylene carbonate (EC), ethyl methyl carbonate (EMC), and fluoroethylene carbonate (FEC). An additional consideration is that NMC90-5-5 undergoes an H2→H3 phase transition that allows for a significant increase to capacity; however, it’s unclear how this phase transition impacts electrolyte stability and cycle life. Therefore, the phase transition is avoided or accessed by cycling to 2.6V or 2.7V, respectively. The cells with Gen2, cycled to 2.6V, show the highest capacity retention due to EC passivating the LTO, EMC improving stability at the NMC90-5-5, and avoiding increased degradation from the 2.7V protocol. Despite having high initial reactivity that causes Li-depletion, FEC was the only solvent to avoid increased degradation when moving to the higher termination voltage.

25 ENERGY STORAGE↗

DOE OSTI2022

Can we use antipredator behavior theory to predict wildlife responses to high-speed vehicles?

Animals seem to rely on antipredator behavior to avoid vehicle collisions. There is an extensive body of antipredator behavior theory that have been used to predict the distance/time animals should escape from predators. These models have also been used to guide empirical research on escape behavior from vehicles. However, little is known as to whether antipredator behavior models are appropriate to apply to an approaching high-speed vehicle scenario. We addressed this gap by (a) providing an overview of the main hypotheses and predictions of different antipredator behavior models via a literature review, (b) exploring whether these models can generate quantitative predictions on escape distance when parameterized with empirical data from the literature, and (c) evaluating their sensitivity to vehicle approach speed using a simulation approach wherein we assessed model performance based on changes in effect size with variations in the slope of the flight initiation distance (FID) vs. approach speed relationship. The slope of the FID vs. approach speed relationship was then related back to three different behavioral rules animals may rely on to avoid approaching threats: the spatial, temporal, or delayed margin of safety. We used literature on birds for goals (b) and (c). Our review considered the following eight models: the economic escape model, Blumstein’s economic escape model, the optimal escape model, the perceptual limit hypothesis, the visual cue model, the flush early and avoid the rush (FEAR) hypothesis, the looming stimulus hypothesis, and the Bayesian model of escape behavior. We were able to generate quantitative predictions about escape distance with the last five models. However, we were only able to assess sensitivity to vehicle approach speed for the last three models. The FEAR hypothesis is most sensitive to high-speed vehicles when the species follows the spatial (FID remains constant as speed increases) and the temporal margin of safety (FID increases with an increase in speed) rules of escape. The looming stimulus effect hypothesis reached small to intermediate levels of sensitivity to high-speed vehicles when a species follows the delayed margin of safety (FID decreases with an increase in speed). The Bayesian optimal escape model reached intermediate levels of sensitivity to approach speed across all escape rules (spatial, temporal, delayed margins of safety) but only for larger (> 1 kg) species, but was not sensitive to speed for smaller species. Overall, no single antipredator behavior model could characterize all different types of escape responses relative to vehicle approach speed but some models showed some levels of sensitivity for certain rules of escape behavior. We derive some applied applications of our findings by suggesting the estimation of critical vehicle approach speeds for managing populations that are especially susceptible to road mortality. Overall, we recommend that new escape behavior models specifically tailored to high-speeds vehicles should be developed to better predict quantitatively the responses of animals to an increase in the frequency of cars, airplanes, drones, etc. they will face in the next decade.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2011

Search for the Standard Model Higgs boson produced in association with a W Boson in the isolated-track charged-lepton channel using the Collider Detector at Fermilab

The Higgs boson is the only elementary particle predicted by the Standard Model (SM) that has not yet been observed experimentally. If it exists, it explains the spontaneous electroweak symmetry breaking and the origin of mass for gauge bosons and fermions. We test the validity of the SM by performing a search for the associated production of a Higgs boson and a W boson in the channel where the Higgs boson decays to a bottom-antibottom quark pair and the W boson decays to a charged lepton and a neutrino (the WH channel). We study a dataset of proton-antiproton collisions at a centre-of-mass energy √s = 1.96 TeV provided by the Tevatron accelerator, corresponding to an integrated luminosity of 5.7 fb -1 , and recorded using the Collider Detector at Fermilab (CDF).We select events consistent with the signature of exactly one charged lepton (electron or muon), missing transverse energy due to the undetected neutrino (MET) and two collimated streams of particles (jets), at least one of which is required to be identified as originating from a bottom quark. We improve the discrimination of Higgs signal from backgrounds through the use of an artificial neural network. Using a Bayesian statistical inference approach, we set for each hypothetical Higgs boson mass in the range 100-150 GeV/c 2 with 5 GeV/c 2 increments a 95% credibility level (CL) upper limit on the ratio between the Higgs production cross section times branching fraction and the SM prediction. Our main original contributions are the addition of a novel charged lepton reconstruction algorithm with looser requirements (ISOTRK) with respect the electron or muon tight criteria (TIGHT), as well as the introduction of a novel trigger-combination method that allows to maximize the event yield while avoiding trigger correlations and that is used for the ISOTRK category. The ISOTRK candidate is a high-transverse-momentum good-quality track isolated from other activity in the tracking system and not required to match a calorimeter cluster, as for a tight electron candidate, or an energy deposit in the muon detector, as for a tight muon candidate. The ISOTRK category recovers real charged leptons that otherwise would be lost in the non-instrumented regions of the detector. This allows the reconstruction of more W boson candidates, which in turn increases the number of reconstructed WH signal candidate events, and therefore improves the sensitivity of the WH search. For the TIGHT charged lepton categories, we employ charged-lepton-dedicated triggers to improve the rate of WH signal acceptance during data taking. Since there is no ISOTRK-dedicated trigger at CDF, for the ISOTRK charged lepton category we employ three MET-plus-jets-based triggers. For each trigger we first identify the jet selection where the trigger efficiency is flat with respect to jet information (transverse energy and direction of motion in the transverse plane for the two jets in the event) and then we parametrize the trigger efficiency as a function of trigger MET. On an event-by-event basis, for each trigger we compute a trigger efficiency as a function of trigger parametrization, trigger MET, jet information, trigger prescale and information about whether the trigger is defined or not. For the ISOTRK category we combine the three triggers using a novel method, which allows the combination of any number of triggers in order to maximize the event yield while avoiding trigger correlations. On an event-by-event basis, only the trigger with the largest efficiency is used. By avoiding a logical 'OR' between triggers, the loss in the yield of events accepted by the trigger combination is compensated by a smaller and easier-to-compute corresponding systematic uncertainty. The addition of the ISOTRK charged lepton category to the TIGHT category produces an increase of 33% in the WH signal yield and a decrease of 15.5% to 19.0% in the median expected 95% CL cross-section upper limits across the entire studied Higgs mass interval. The improvement in analysis sensitivity is smaller than the improvement in signal yield because the ISOTRK category has a smaller signal over background ratio than the TIGHT category, due to the looser ISOTRK reconstruction criteria. The observed (median expected) 95% CL SM Higgs upper limits on cross section times branching ratio vary between 2.39 x SM (2.73 x SM) for a Higgs mass of 100 GeV/c 2 to 31.1 x SM (31.2 x SM) for a Higgs mass of 150 GeV/c 2 , while the value for a 115 GeV/c 2 Higgs boson is that of 5.08 x SM (3.79 x SM). The novel trigger combination method is already in use by several CDF analyses. It is applicable to any analysis that uses triggers based on MET and jets, such as supersymmetry searches at the ATLAS and CMS experiments at the Large Hadron Collider. In its most general form, the method can be used by any analysis that combines any number of different triggers.

43 PARTICLE ACCELERATORS↗

DOE OSTI2015

Value of Solar. Program Design and Implementation Considerations

Here, we present an analysis that assesses the potential market type that might form in the United States under a VOS rate, given current national average solar costs and various incentive scenarios, for the most populous city in each state. Three hypothetical VOS tariffs were developed, based on assumptions of avoided fuel costs, avoided capacity, environmental benefits, and line losses, to represent a of range of possible VOS rates. The levelized cost of solar in 50 locations is calculated using NREL’s System Advisor Model (SAM) using input assumptions regarding system size, resource quality, avoided capacity (aka capacity factor) and a variety of incentives. Comparing the solar costs with the hypothetical VOS rates illustrates the various market types that may form under a VOS program, in different locations.

14 SOLAR ENERGY↗

DOE OSTI2015

Operational Benefits of Meeting California's Energy Storage Targets

In October 2013, the California Public Utilities Commission (CPUC) finalized procurement targets and other requirements to its jurisdictional utilities for a minimum of 1,325 MW of 'viable and cost-effective' energy storage systems by 2020. The goal of this study is to explore several aspects of grid operations in California and the Western Interconnection resulting from meeting the CPUC storage targets. We perform this analysis using a set of databases and grid simulation tools developed and implemented by the CPUC, the California Independent System Operator (CAISO), and the California Energy Commission (CEC) for the CPUC's Long-term Procurement Plan (LTPP). The 2014 version of this database contains information about generators, storage, transmission, and electrical demand, for California in the year 2024 for both 33% and 40% renewable energy portfolios. We examine the value of various services provided by energy storage in these scenarios. Sensitivities were performed relating to the services energy storage can provide, the capacity and duration of storage devices, export limitations, and negative price floor variations. Results show that a storage portfolio, as outlined by the CPUC, can reduce curtailment and system-wide production costs for 33% and 40% renewable scenarios. A storage device that can participate in energy and ancillary service markets provides the grid with the greatest benefit; the mandated storage requirement of 1,325 MW was estimated to reduce the total cost of production by about 78 million per year in the 33% scenario and 144 million per year in the 40% scenario. Much of this value is derived from the avoided start and stop costs of thermal generators and provision of ancillary services. A device on the 2024 California grid and participating in only ancillary service markets can provide the system with over 90% of the value as the energy and ancillary service device. The analysis points to the challenge of new storage providing regulation reserve, as the added storage could provide about 75% of the regulation up requirement for all of California, which would likely greatly reduce regulation prices and potential revenue. The addition of storage in California decreases renewable curtailment, particularly in the 40% RPS case. Following previous analysis, storage has a mixed impact on emissions, generally reducing emissions, but also creating additional incentives for increased emissions from out-of-state coal generations. Overall, storage shows significant system cost savings, but analysis also points to additional challenges associated with full valuation of energy storage, including capturing the operational benefits calculated here, but also recovering additional benefits associated avoided generation, transmission, and distribution capacity, and avoided losses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2018

Nebraska Integrated Carbon Capture and Storage Pre-Feasibility Study

In collaboration with the Nebraska Public Power District (NPPD), the Energy & Environmental Research Center (EERC) has conducted a pre-feasibility study for a commercial-scale carbon dioxide (CO 2 ) geologic storage complex in western Nebraska integrated with potential CO 2 capture at Gerald Gentleman Station (GGS). GGS is the largest coal-fired electricity-generating station in Nebraska, emitting 8.5 million metric tons (Mt) of CO 2 annually, and is located near the town of Sutherland. This pre-feasibility (Phase 1) project has been executed as part of the U.S. Department of Energy (DOE) CarbonSAFE program, a multiphase initiative to support the deployment of large-scale carbon capture and storage (CCS) projects. Each CarbonSAFE project is required to demonstrate the potential to capture and store at least 50 million tonnes (Mt) of CO 2 over a 25-year operational period. The EERC and NPPD established a coordination team to identify challenges to a potential Nebraska CCS project, comprising local stakeholder organizations, which met twice in Lincoln and via several Webinars, providing feedback and guidance throughout the pre-feasibility study. The EERC also secured the technical support of Schlumberger Carbon Services and Computer Modelling Group Ltd. (CMG). The project comprised four technical themes, all using published information sources. Regional and stakeholder analysis, including identification of sensitive environmental areas, potential resource conflicts, and strategies for public outreach. A review of geographic and socioeconomic characteristics, in combination with geologic characterization in the subbasinal analysis described below, identified an area to the southwest and within a 75-mile radius of GGS as the most prospective for development of a storage site. This area largely avoided lands with protected status such as wetlands. A public outreach plan has also been developed for implementation in any further phases of CCS assessment in western Nebraska, for example a CarbonSAFE Phase 2 feasibility study. Scenario analysis, addressing economic and regulatory factors. GGS is the only single major source of CO 2 emissions capable of satisfying the CarbonSAFE 50-Mt scale requirement within the study region. Chemical absorption using amines was identified as the most viable technology for postcombustion CO 2 capture at GGS. The total cost of a CCS project at GGS was estimated to be between $67/tonne CO 2 for capture and auxiliary boiler to minimize parasitic load and $70/tonne CO 2 avoided cost, using the Carnegie-Mellon University Integrated Environmental Control Model (IECM). The total avoided cost included the capture facility and parasitic load, a flue gas desulfurization plant required for the use of amine solvent technology, transport via pipeline, and dedicated storage infrastructure. Nebraska has no legislation in place to address typical CCS-specific issues, for example pore space ownership for storage. Long-term liability, therefore, falls under the U.S. Environmental Protection Agency Underground Injection Control (UIC) Class 6 program regulations. Subbasinal analysis, addressing the potential for a dedicated subsurface “container” to store the required 50-Mt quantity of CO 2 . Modeling and simulation studies identified an area to the southwest of GGS with the potential for storage of 50 Mt CO 2 in the Cloverly Formation, comprising sandstones with interbedded and intermingled shales. The area of review (AOR) that would be required for monitoring under a Class VI operating permit was estimated to be as high as 400–700 square miles, due to uncertain pressure effects. The viability of this storage option is subject to significant uncertainty due to the relatively limited amount of existing characterization data available to the pre-feasibility study; for example, dynamic simulation indicated that the proposed storage rate might require as little as two or as many as 14 injection wells. A key uncertainty is the relative proportion and distribution of sandstone and shale within the Cloverly Formation. A preliminary, semiquantitative risk assessment also suggested uncertainty over storage capacity and injectivity constitute the most significant project risks at this pre-feasibility stage. No assessed risks were considered to rule out the possibility of a project moving to deployment. National Risk Assessment Partnership (NRAP) validation, using software tools developed by the National Energy Technology Laboratory (NETL) to assess risks associated with the potential 50-Mt CO 2 storage complex. NRAP tools were used to assess hypothetical leakage scenarios. Results broadly supported the conclusion of the semiquantitative risk analysis – for example, even worst-case analysis of theoretical leakage scenarios found limited migration rates and impacts. In summary, the work undertaken in this Phase 1 pre-feasibility study has shown that western Nebraska has potential to host a commercial-scale CCS project, including a dedicated storage “container” for 50 Mt of CO 2 . However, the following key challenges would need to be overcome: The business case for deploying CCS projects is uncertain; recently announced federal tax credits and sales of CO 2 for enhanced oil recovery may not cover the full costs of a CCS project at GGS, as estimated by this pre-feasibility study. The potential 50-Mt CO 2 dedicated storage container defined in this pre-feasibility study should be regarded as having a relatively low level of readiness to support a CCS project. Public outreach would be a vital element in western Nebraska, where sensitivities around such environmental issues as water resource protection and pipeline construction would need to be carefully addressed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Financing Microgrids in the Federal Sector

Recent high-impact events such as hurricanes and wildfires highlight the need for energy system resilience. One potential impact of these events is the loss of utility grid power to federal sites, negatively affecting the ability to carry out their missions. Depending on the need to sustain critical functions, it may be important to continue operations during an outage of the electric grid, or at least have power restored quickly after the event. One approach to addressing this need is through a microgrid. Microgrids can provide a more reliable solution than the traditional approach of using a backup generator at individual buildings. A microgrid can enhance a site’s electrical power system during normal operations, as well as provide reliable backup power to critical loads when electric utility power is interrupted. Many times, certain components of a microgrid (and potentially the entire system) can be justified economically and paid for out of energy savings or avoided costs. In cases where savings can cover the project costs, one of several privately financed procurement mechanisms may be used to implement the project. Procurement options available to all federal agencies include utility energy services contracts (UESC), energy savings performance contracts (ESPC), and utility services contracts (USC); other mechanisms such as a power purchase agreement (PPA), enhanced use lease (EUL), and utility privatization (UP) may also be useful to agencies that have the authority to use them. Implementing a microgrid in a comprehensive effort that also includes energy efficiency can provide an important savings component, while reducing power requirements for critical loads, thus reducing the cost of the microgrid and associated distributed energy resources (DER). However, it can be difficult to achieve enough savings and avoided costs to cover the entire microgrid system, so leveraging these avoided costs in combination with appropriated funds may be necessary to implement the full project. When a site is deciding if a microgrid is the best solution, activities early in the process include identifying critical loads and existing DERs, conversations with the local electric utility, and implementation options that work best for the agency and site. This paper explores procurement options and agreements that may be useful to federal agencies interested in implementing microgrids at their sites. Microgrid complexities, implementation considerations, and suggestions to get started are also discussed. This information will be most useful to agencies when they are exploring electric energy system resilience options and/or considering different procurement options to meet their needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Financing Microgrids in the Federal Sector

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Real-Time Drilling Optimization System for Improved Overall Rate of Penetration and Reduced Cost Per Foot in Geothermal Drilling

The key to success in geothermal drilling is economic feasibility, and a major cost in the development of geothermal resources is the actual drilling of the wells. In this project, a real-time drilling optimization system for geothermal drilling was developed. The system couples three individual components while drilling. The first component is a drill stem vibration analysis model, the second is Mechanical Specific Energy (MSE) analyses, and the third is a detailed PDC Rate of Penetration (ROP) drill bit model for optimum RPM and WOB combinations. The benefit of the coupled system is that the range of WOB and RPM could be selected to avoid drill stem vibrations. Secondly, MSE is used as an efficiency measure and the detailed PDC drill bit model ensures the drill bit does not endure temperatures that exceed the temperature at which the PDC cutters experience accelerated wear. The new detailed PDC bit model is based on rock/bit interaction that physically tracks the PDC cutter wear flats as the bit drills ahead giving the capability to calculate the temperature being generated underneath the worn cutters to better advise on operational parameters to avoid accelerated cutter wear and failure and to ensure that operational parameters are applied so that overall ROP is maximized. By combining the drill stem vibrations and the detailed PDC bit cutter wear and “safe” non-accelerated cutter wear temperature and optimum ranges of operating parameters, it results in higher ROP and lower cost drilling. Single cutter PDC testing performed in different lithologies at Sandia was utilized to verify the PDC cutter forces and depth of cut for new and worn cutters. Based on single cutter PDC temperature modeling, verification using single cutter data from the testing done by National Oilwell Varco (NOV) was performed. Sandia’s Hard-Rock Drilling Facility (HRDF) was utilized to test different drill bit configurations with different cutter designs and wear status with different induced modes of vibration to obtain the critical bit RPM/WOB ranges resulting in ineffective drilling and low ROP. The collected test data were further used to verify and calibrate the full hole PDC ROP model that was developed based on single cutter interaction data. A full coupled drill stem vibration model was formulated and verified with geothermal field data from the Chocolate Mountain Aerial Gunnery Range (CMAGR). A graphical user interface (GUI) was developed using Tkinter library in the computer programming language Python, which integrates all the developed models in one system. The developed system consists mainly of the PDC ROP model, PDC bit wear model, PDC cutter temperature model, Mechanical Specific Energy (MSE) model, and drillstring vibration model integrated into one system. The developed system can be used for both, post well analysis and real-time optimization using different criteria such as ROP maximization or MSE minimization. The software uses Differential Evolution Algorithm (DEA) to find optimum values for operational parameters based on last foot drilled while avoiding the drillstring vibration and cutter temperature critical operating parameters.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Quantifying conditional probabilities of fish-turbine encounters and impacts

Tidal turbines are one source of marine renewable energy but development of tidal power is hampered by uncertainties in fish-turbine interaction impacts. Current knowledge gaps exist in efforts to quantify risks, as empirical data and modeling studies have characterized components of fish approach and interaction with turbines, but a comprehensive model that quantifies conditional occurrence probabilities of fish approaching and then interacting with a turbine in sequential steps is lacking. We combined empirical acoustic density measurements of Pacific herring ( Clupea pallasii ) and when data limited, published probabilities in an impact probability model that includes approach, entrainment, interactions, and avoidance of fish with axial or cross-flow tidal turbines. Interaction impacts include fish collisions with stationary turbine components, blade strikes by rotating blades, and/or a collision followed by a blade strike. Impact probabilities for collision followed by a blade strike were lowest with estimates ranging from 0.0000242 to 0.0678, and highest for blade strike ranging from 0.000261 to 0.40. Maximum probabilities occurred for a cross-flow turbine at night with no active or passive avoidance. Estimates were lowest when probabilities were conditional on sequential events, and when active and passive avoidance was included for an axial-flow turbine during the day. As expected, conditional probabilities were typically lower than analogous independent events and literature values. Estimating impact probabilities for Pacific herring in Admiralty Inlet, Washington, United States for two device types illustrates utilization of existing data and simultaneously identifies data gaps needed to fully calculate empirical-based probabilities for any site-species combination.

collision risk↗

DOE OSTI2023

Uncertainty quantification of machine learning models to improve streamflow prediction under changing climate and environmental conditions

Machine learning (ML) models, and Long Short-Term Memory (LSTM) networks in particular, have demonstrated remarkable performance in streamflow prediction and are increasingly being used by the hydrological research community. However, most of these applications do not include uncertainty quantification (UQ). ML models are data driven and can suffer from large extrapolation errors when applied to changing climate/environmental conditions. UQ is required to quantify the influence of data noises on model predictions and avoid overconfident projections in extrapolation. In this work, we integrate a novel UQ method, called PI3NN, with LSTM networks for streamflow prediction. PI3NN calculates Prediction Intervals by training 3 Neural Networks. It can precisely quantify the predictive uncertainty caused by the data noise and identify out-of-distribution (OOD) data in a non-stationary condition to avoid overconfident predictions. We apply the PI3NN-LSTM method in the snow-dominant East River Watershed in the western US and in the rain-driven Walker Branch Watershed in the southeastern US. Results indicate that for the prediction data which have similar features as the training data, PI3NN precisely quantifies the predictive uncertainty with the desired confidence level; and for the OOD data where the LSTM network fails to make accurate predictions, PI3NN produces a reasonably large uncertainty indicating that the results are not trustworthy and should avoid overconfidence. PI3NN is computationally efficient, robust in performance, and generalizable to various network structures and data with no distributional assumptions. It can be broadly applied in ML-based hydrological simulations for credible prediction.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Addressing numerical challenges in introducing a reactive transport code into a land surface model: a biogeochemical modeling proof-of-concept with CLM–PFLOTRAN 1.0

Abstract. We explore coupling to a configurable subsurface reactive transport code as a flexible and extensible approach to biogeochemistry in land surface models. A reaction network with the Community Land Model carbon–nitrogen (CLM-CN) decomposition, nitrification, denitrification, and plant uptake is used as an example. We implement the reactions in the open-source PFLOTRAN (massively parallel subsurface flow and reactive transport) code and couple it with the CLM. To make the rate formulae designed for use in explicit time stepping in CLMs compatible with the implicit time stepping used in PFLOTRAN, the Monod substrate rate-limiting function with a residual concentration is used to represent the limitation of nitrogen availability on plant uptake and immobilization. We demonstrate that CLM–PFLOTRAN predictions (without invoking PFLOTRAN transport) are consistent with CLM4.5 for Arctic, temperate, and tropical sites.Switching from explicit to implicit method increases rigor but introduces numerical challenges. Care needs to be taken to use scaling, clipping, or log transformation to avoid negative concentrations during the Newton iterations. With a tight relative update tolerance (STOL) to avoid false convergence, an accurate solution can be achieved with about 50 % more computing time than CLM in point mode site simulations using either the scaling or clipping methods. The log transformation method takes 60–100 % more computing time than CLM. The computing time increases slightly for clipping and scaling; it increases substantially for log transformation for half saturation decrease from 10-3 to 10-9 mol m-3, which normally results in decreasing nitrogen concentrations. The frequent occurrence of very low concentrations (e.g. below nanomolar) can increase the computing time for clipping or scaling by about 20 %, double for log transformation. Overall, the log transformation method is accurate and robust, and the clipping and scaling methods are efficient. When the reaction network is highly nonlinear or the half saturation or residual concentration is very low, the allowable time-step cuts may need to be increased for robustness for the log transformation method, or STOL may need to be tightened for the clipping and scaling methods to avoid false convergence.As some biogeochemical processes (e.g., methane and nitrous oxide reactions) involve very low half saturation and thresholds, this work provides insights for addressing nonphysical negativity issues and facilitates the representation of a mechanistic biogeochemical description in Earth system models to reduce climate prediction uncertainty.

58 GEOSCIENCES↗

DOE OSTI2018

Identifying Sociomarkers of Pediatric Asthma Patients at Risk of Hospital Revisiting

ObjectiveAsthma is one of the most common chronic childhood diseases in the United States [2, 3]. In addition to its pervasiveness, pediatric asthma shows high sensitivity to the environment. Combining medical-social dataset with machine learning methods we demonstrate how socio-markers play an important role in identifying patients at risk of hospital revisits due to pediatric asthma within a year.IntroductionA socio-marker is a measurable indicator of social conditions where a patient is embedded in and exposed to, being analogous with a biomarker indicating the severity or presence of some disease state. Social factors are one of the most clinical health determinants [1], which play a critical role in explaining health outcomes. Socio-markers can help medical practitioners and researchers to reliably identify high-risk individuals in a timely manner.MethodsWe collected data from three different sources: pediatric asthma encounter records from Jan 1st, 2016 to Dec 31st, 2016 at a children’s hospital, the 2010 U.S census data and neighborhood quality survey data by Memphis Property Hub. After merging these datasets we examine the effect of social features in identifying the patients who visited the hospital more than once during the observation period. We only use the first time visit (3,678 cases) to avoid over-counting of the same patients. In addition to demographic features (age, gender, insurance type, and race (African American and White)), we incorporate the social features such as the proportion of individuals living below the federal poverty level, blight prevalence, neighborhood quality, neighborhood quality inequality, trash dumping presence, the broken window pervasiveness within the zip code area of patients’ residence are included.We then implemented a Support Vector Machine (SVM) based classification model using abovementioned 11 social features. The classification outcome is either patient visits the hospital only one-time (class 0) or revisits the hospital within a year (class 1). Among 3,678 unique patients in the dataset, only 823 pediatric patients revisited hospital with asthma. So, to overcome the class imbalance issue, we have used 823 patients’ data (randomly selected in 1,000 iterations) from each class. Further, to avoid overfitting and ensure generalizability, we divided the dataset as training, test, and validation with a proportion of 60%, 20%, and 20%, respectively. The reported test (5-folds cross-validation using training and testing data) and validation accuracy of the SVM method are averaged over 1,000 iterations to avoid sampling error and bias.ResultsThe proposed socio-marker model resulted in an average classification accuracy of 63.70% for the test set and 63.67 % for the validation set. Further, the average specificity (the total true negative cases divided by the sum of true negative and false positive) and sensitivity (the total number of true positive cases divided by the sum of positive predicted cases) is found to be 62.79% and 64.77%, respectively for the test set and 62.79% and 64.83%, respectively for the validation set. Results of this study suggest that socio-marker features that are not directly related to a patient’s medical conditions can still predict whether the patient will come back to the hospital within a year or not with approximately 64% accuracy.ConclusionsBringing the socio-marker features in the surveillance system may ease the burden of detecting the patients at risk of revisiting the hospital. The results should be interpreted with caution because we only used 12-month period of observation and the visit beyond the observation window is not considered. Also the patients may have visited different hospitals which are not captured in the data.References1. Booske BC, Athens JK, Kindig DA, Park H, Remington PL: Different perspectives for assigning weights to determinants of health. University of Wisconsin: Population Health Institute 2010.2. Subbarao P, Mandhane PJ, Sears MR: Asthma: epidemiology, etiology and risk factors. Canadian Medical Association Journal 2009, 181(9):E181-E190.3. Gold DR, Wright R: Population disparities in asthma. Annu Rev Public Health 2005, 26:89-113.

Shin, Eun Kyong↗

NASA NTRS1981

Operational evaluation of thunderstorm penetration test flights during project Storm Hazards '80

The National Aeronautics and Space Administration is conducting a research project called Storm Hazards '80 in order to study the prediction, detectability and avoidance of the hazards of severe storms for aircraft operations. The project, using a highly instrumented NASA F-106B airplane to penetrate thunderstorms, gathered and correlated data from both airborne and ground based instrumentation. The objectives of this project are to determine the effects of lightning on the design and operation of aircraft composite structures and digital electronic systems. The data will be used to determine the correlation of lightning hazards with other severe storm hazards, such as heavy precipitation, hail, turbulence and wind-shear, in order to develop an initial data base for use in design and avoidance. The NASA F-106B was equipped with a weather radar, stormscope, lightning measurement instrumentation and air sampling equipment. This paper will focus on the operational aspects of thunderstorm penetrations and the pilot techniques used to avoid the extremely hazardous portions of the storm such as the tornadoes and hail. It will deal with the effects of the storm elements on the aircraft hardware, avionics and the crew.

Keyser, G. L., Jr.↗

NASA NTRS1982

Mission analysis techniques for attached Shuttle payloads

Visibility times, i.e., times which desired targets are visible to a payload, are examined for attached Shuttle payloads. These times are affected by a number of constraints. Some constraints are examined along with mathematical or computer modeling techniques used to determine their effects. The constraints include: occultation of the earth, moon, and sun, and limb avoidance angles of each; orbit parameters such as inclination and ascending node, along with sensitivity to changes in each; TDRSS acquisition; South Atlantic Anomaly (SAA) avoidance, nighttime viewing only; bright earth avoidance angles; the field of view; Shuttle attitude, and Orbiter operational constraints. All of this information is integrated and, with computer programs, a schedule of observations and Shuttle attitudes is obtained.

Lambros, S.↗

NASA NTRS1983

Conflict resolution maneuvers during near miss encounters with cockpit traffic displays

The benefits and liabilities associated with pilots' use of a cockpit traffic display to assess the threat posed by air traffic and to make small maneuvers to avoid situations which would result in collision avoidance advisories are experimentally studied. The crew's task was to fly a simulated wide-body aircraft along a straight course at constant altitude while intruder aircraft appeared on a variety of converging trajectories. The main experimental variables were the amount and quality of the information displayed on the intruder aircraft's estimated future position. Pilots were to maintain a horizontal separation of at least 1.5 nautical miles or a vertical separation of 500 ft, so that collision avoidance advisories would not be triggered. The results show that pilots could usually maneuver to provide the specified separation but often made course deviations greater than 1.5 nm or 500 ft.

Palmer, E.↗

NASA NTRS1987

Collision-free motion of two robot arms in a common workspace

Collision-free motion of two robot arms in a common workspace is investigated. A collision-free motion is obtained by detecting collisions along the preplanned trajectories using a sphere model for the wrist of each robot and then modifying the paths and/or trajectories of one or both robots to avoid the collision. Detecting and avoiding collisions are based on the premise that: preplanned trajectories of the robots follow a straight line; collisions are restricted to between the wrists of the two robots (which corresponds to the upper three links of PUMA manipulators); and collisions never occur between the beginning points or end points on the straight line paths. The collision detection algorithm is described and some approaches to collision avoidance are discussed.

Basta, Robert A.↗