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At least 973 records · Page 54

All sources NASA NTRS DOE OSTI

DOE OSTI2016

Large-scale inference of gene function through phylogenetic annotation of Gene Ontology terms: case study of the apoptosis and autophagy cellular processes

We previously reported a paradigm for large-scale phylogenomic analysis of gene families that takes advantage of the large corpus of experimentally supported Gene Ontology (GO) annotations. This ‘GO Phylogenetic Annotation’ approach integrates GO annotations from evolutionarily related genes across 100 different organisms in the context of a gene family tree, in which curators build an explicit model of the evolution of gene functions. GO Phylogenetic Annotation models the gain and loss of functions in a gene family tree, which is used to infer the functions of uncharacterized (or incompletely characterized) gene products, even for human proteins that are relatively well studied. Here, we report our results from applying this paradigm to two well-characterized cellular processes, apoptosis and autophagy. This revealed several important observations with respect to GO annotations and how they can be used for function inference. Notably, we applied only a small fraction of the experimentally supported GO annotations to infer function in other family members. The majority of other annotations describe indirect effects, phenotypes or results from high throughput experiments. In addition, we show here how feedback from phylogenetic annotation leads to significant improvements in the PANTHER trees, the GO annotations and GO itself. Thus GO phylogenetic annotation both increases the quantity and improves the accuracy of the GO annotations provided to the research community. We expect these phylogenetically based annotations to be of broad use in gene enrichment analysis as well as other applications of GO annotations.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2016

Earthdata Search Client: Usability Review Process, Results, and Implemented Changes, Using Earthdata Search Client as a Case Study

User experience and visual design are greatly improved when usability testing is performed on a periodic basis. Design decisions should be tested by real users so that application owners can understand the effectiveness of each decision and identify areas for improvement. It is important that applications be tested not just once, but as a part of a continuing process that looks to build upon previous tests. NASA's Earthdata Search Client has undergone a usability study to ensure its users' needs are being met and that users understand how to use the tool efficiently and effectively. This poster will highlight the process followed for usability study, the results of the study, and what has been implemented in light of the results to improve the application's interface.

design↗

DOE OSTI2013

New Whole-House Solutions Case Study: Affordable Cold Climate Infill Housing with Hybrid Insulation Approach, Wyandotte, Michigan

Even builders who are relatively new to energy-efficient construction can consistently reach a target whole house airtightness of 1.5 air changes per hour at 50 Pascals (ACH50) with high R-value enclosures that use a hybrid insulation approach. In 2010, the City of Wyandotte, Michigan, started construction to build affordable, energy-efficient homes on lots in existing neighborhoods. A goal was to engage local builders in energy-efficient construction and be able to deliver the new houses for less than $100/ft2. By the end of 2012, approximately 25 new houses were built by five local builders under this program. To help builders consistently achieve the airtightness target, a local architect worked with researchers from Building Science Corporation, a Building America team, to develop a technology specification with several key pieces. A high R-value wall and roof assembly made use of 2 ×6 advanced framing and a hybrid insulation approach that included insulating sheathing to control thermal bridging and closed cell spray polyurethane foam insulation (ccSPF) for its airtightness and vapor control benefits. This approach allows the air barrier to be completed and tested before any finishing work occurs, ensuring that problems are spotted and corrected early in the construction process.

BSC↗

DOE OSTI2024

Assessment of Technoeconomic Opportunities in Automation for Nuclear Microreactors

Achieving full decarbonization of all economic sectors remains a challenge, especially in niche markets. For example, remote communities and industrial or mining activities detached from the main electric grid heavily rely on fossil fuels, similar to urban and industrial microgrids with combined heat and power needs. A combination of renewables and energy storage is often not suitable due to cost, reliability, intermittency, and large storage requirements. Small nuclear reactors with a flexible purpose could serve these applications. Microreactors (MR) are a class of reactors that are compact, factory manufactured, transportable, and self-regulating. Typically, they generate much less power than their large reactor counterparts. The main advantages of microreactors include the versatile nature of the energy produced, the reliability of supply, and freedom from having to transport and store large quantities of fuels on-site, coupled with the absence of dependence on an electrical grid. A strong business case is needed to move from the microreactor prototype to the commercialization phase. In fact, fossil fuels are still relatively inexpensive, and in the near term, carbon credits will be available to virtually compensate for emissions. For microreactors, one of the main costs in operation and maintenance (O&M) is their staffing levels. In this study, we investigate how to optimize the number (and thus the cost) of workers, moving from a traditional, fully manned, on-site personnel approach to an unmanned, remote personnel approach. We examine four different staffing models that can be implemented as the technology matures and evolves. We estimate the staffing needs of each model and build a business case to justify the substitution of on-site personnel with adequate technologies. To do so, we propose a cost model to quantify potential cost reductions from automating O&M activities. The model accounts for both the reduction in cost derived from the reduced number of full-time-equivalent (FTE) employees and the increase in cost derived from the need to buy new control hardware as needed. Applying the cost model that we created to different scenarios, an on-site O&M cost reduction exceeding 80% can be expected. Additionally, we found that it is more impactful to focus on automating routine O&M tasks rather than attempting to automate transient management (shutdowns, restarts, monitoring condition deviations). In fact, transients typically account for less than 1% of the total FTE time spent on the reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2019

Enabling immersive engagement in energy system models with deep learning

Complex ensembles of energy simulation models have become crucial components of renewable energy research in recent years. Often the increasing computational cost, high-dimensional structure, and other complexities hinder researchers from fully utilizing these data sources for knowledge building. Researchers at National Renewable Energy Laboratory have determined an immersive visualization workflow to dramatically improve user engagement and analysis capability through a combination of low-dimensional structure analysis, deep learning, and custom visualization methods. We present case studies for two energy simulation platforms.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Economic Analysis and Optimal Sizing for behind-the-meter Battery Storage

This paper proposes methods to estimate the potential benefits and determine the optimal energy and power capacity for behind-the-meter BSS. In the proposed method, a linear programming is first formulated only using typical load profiles, energy/demand charge rates, and a set of battery parameters to determine the maximum saving in electric energy cost. The optimization formulation is then adapted to include battery cost as a function of its power and energy capacity in order to capture the trade-off between benefits and cost, and therefore to determine the most economic battery size. Using the proposed methods, economic analysis and optimal sizing have been performed for a few commercial buildings and utility rate structures that are representative of those found in the various regions of the Continental United States. The key factors that affect the economic benefits and optimal size have been identified. The proposed methods and case study results cannot only help commercial and industrial customers or battery vendors to evaluate and size the storage system for behind-the-meter application, but can also assist utilities and policy makers to design electricity rate or subsidies to promote the development of energy storage.

Wu, Di↗

DOE OSTI2016

SU-F-T-474: Evaluation of Dose Perturbation, Temperature and Sensitivity Variation With Accumulated Dose of MOSFET Detector

Purpose: The use of mega voltage gamma and x-ray sources with their skin sparring qualities in radiation therapy has been a boon in relieving patient discomfort and allowing high tumor doses to be given with fewer restrictions due to radiation effects in the skin. However, high doses given to deep tumors may require careful consideration of dose distribution in the buildup region in order to avoid irreparable damage to the skin. Methods: To measure the perturbation of MOSFET detector in Co60,6MV and 15MV the detector was placed on the surface of the phantom covered with the brass build up cap. To measure the effect of temperature the MOSFET detector was kept on the surface of hot water polythene container and the radiation was delivere. In order to measure the sensitivity variation with accumulated dose Measurements were taken by delivering the dose of 200 cGy to MOSFET until the MOSFET absorbed dose comes to 20,000 cGy Results: the Measurement was performed by positioning the bare MOSFET and MOSFET with brass build up cap on the top surface of the solid water phantom for various field sizes in order to find whether there is any attenuation caused in the dose distribution. The response of MOSFET was monitored for temperature ranging from 42 degree C to 22 degree C. The integrated dose dependence of MOSFET dosimeter sensitivity over different energy is not well characterized. This work investigates the dual-bias MOSFET dosimeter sensitivity response to 6 MV and 15 MV beams. Conclusion: From this study it is observed that unlike diode, bare MOSFET does not perturb the radiation field.. It is observed that the build-up influences the temperature dependency of MOSFET and causes some uncertainty in the readings. In the case of sensitivity variation with accumulated dose MOSFET showed higher sensitivity with dose accumulation for both the energies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Control Strategies to Reduce the Energy Consumption of Central Domestic Hot Water Systems

Domestic hot water (DHW) heating is the second largest energy end use in U.S. buildings, exceeded only by space conditioning. Recirculation systems consisting of a pump and piping loop(s) are commonly used in multifamily buildings to reduce wait time for hot water at faucets; however, constant pumping increases energy consumption by exposing supply and return line piping to continuous heat loss, even during periods when there is no demand for hot water. In this study, ARIES installed and tested two types of recirculation controls in a pair of buildings in order to evaluate their energy savings potential. Demand control, temperature modulation controls, and the simultaneous operation of both were compared to the baseline case of constant recirculation. Additionally, interactive effects between DHW control fuel reductions and space conditioning (heating and cooling) were estimated in order to make more realistic predictions of the payback and financial viability of retrofitting DHW systems with these controls. Results showed that DHW fuel consumption reduced by 7% after implementing the demand control technique, 2% after implementing temperature modulation, and 15% after implementing demand control and temperature modulation techniques simultaneously; recirculation pump runtime was reduced to 14 minutes or less per day. With space heating and cooling interactions included, the estimated annual cost savings were 8%, 1%, and 14% for the respective control techniques. Possible complications in the installation, commissioning and operation of the controls were identified and solutions offered.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

Control Strategies to Reduce the Energy Consumption of Central Domestic Hot Water Systems

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Recommended Target Fields for Commissioning the Vera C. Rubin Observatory

The commissioning team for the Vera C. Rubin observatory is planning a set of engineering and science verification observations with the Legacy Survey of Space and Time (LSST) commissioning camera and then the Rubin Observatory LSST Camera. The time frame for these observations is not yet fixed, and the commissioning team will have flexibility in selecting fields to observe. In this document, the Dark Energy Science Collaboration (DESC) Commissioning Working Group presents a prioritized list of target fields appropriate for testing various aspects of DESC-relevant science performance, grouped by season for visibility from Rubin Observatory at Cerro Pachon. Our recommended fields include Deep-Drilling fields (DDFs) to full LSST depth for photo-$z$ and shape calibration purposes, HST imaging fields to full depth for deblending studies, and an $\sim$200 square degree area to 1-year depth in several filters for higher-level validation of wide-area science cases for DESC. We also anticipate that commissioning observations will be needed for template building for transient science over a broad RA range. We include detailed descriptions of our recommended fields along with associated references. We are optimistic that this document will continue to be useful during LSST operations, as it provides a comprehensive list of overlapping data-sets and the references describing them.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Examination of Extreme Rainfall Events in Two Regions of the United States since the 19th Century

A common hypothesis regarding human-induced climate change is that precipitation processes will accelerate leading to an increasing magnitude of rainfall amounts on a daily time scale as the atmosphere warms. This assertion is supported by two physically demonstrable facts, (1) warmer air accommodates more water vapor, and (2) precipitation processes become more efficient as the cloud environment warms. However, by definition, extreme events are rare, and thus statistics of their occurrence and possible long-term changes present difficult challenges, some herein addressed. In any case, the observational datasets on which hypothesis tests may be carried out should cover the longest periods possible because precipitation can naturally vary considerably on even century time scales. In this study we focus on this temporal issue by building long-term daily precipitation datasets for twenty stations, ten along or near the US Pacific Coast (PC) and ten along or near the coast in the US Southeast (SE). Observations for these stations begin between 1840 and 1890 and end in 2018, using the water year (Oct to Sep) to define the annual period. For some metrics, e.g. the annual total precipitation or the number of days per year measuring greater than 25 mm, there is no discernable change over the most recent 145 years (1874-2018). For other metrics, e.g. the magnitude of the wettest day per year or the temporal distribution of the 29 wettest 2-day events in the past 145 years (i.e. nominal 1-in-5-year occurrence), there appears to be an increase in SE and a decrease in PC. Whether these trends are significant for the relatively short climate record of 145 years will be discussed with the conclusion being the limited time frame of analysis does not lead to decisive claims that these changes are outside of the range of natural variability.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2012

NASA's Space Launch System Progress Report

Exploration beyond Earth orbit will be an enduring legacy for future generations, as it provides a platform for science and exploration that will define new knowledge and redefine known boundaries. NASA s Space Launch System (SLS) Program, managed at the Marshall Space Flight Center, is responsible for designing and developing the first exploration-class rocket since the Apollo Program s Saturn V that sent Americans to the Moon in the 1960s and 1970s. The SLS offers a flexible design that may be configured for the Orion Multi-Purpose Crew Vehicle with associated life-support equipment and provisions for long journeys or may be outfitted with a payload fairing that will accommodate flagship science instruments and a variety of high-priority experiments. Building on legacy systems, facilities, and expertise, the SLS will have an initial lift capability of 70 tonnes (t) in 2017 and will be evolvable to 130 t after 2021. While commercial launch vehicle providers service the International Space Station market, this capability will surpass all vehicles, past and present, providing the means to do entirely new missions, such as human exploration of Mars. Building on the foundation laid by over 50 years of human and scientific space flight and on the lessons learned from the Apollo, Space Shuttle, and Constellation Programs the SLS team is delivering both technical trade studies and business case analyses to ensure that the SLS architecture will be safe, affordable, reliable, and sustainable. This panel will address the planning and progress being made by NASA s SLS Program.

May, Todd A.↗

DOE OSTI2014

Using computer-extracted image features for modeling of error-making patterns in detection of mammographic masses among radiology residents

Purpose: Mammography is the most widely accepted and utilized screening modality for early breast cancer detection. Providing high quality mammography education to radiology trainees is essential, since excellent interpretation skills are needed to ensure the highest benefit of screening mammography for patients. The authors have previously proposed a computer-aided education system based on trainee models. Those models relate human-assessed image characteristics to trainee error. In this study, the authors propose to build trainee models that utilize features automatically extracted from images using computer vision algorithms to predict likelihood of missing each mass by the trainee. This computer vision-based approach to trainee modeling will allow for automatically searching large databases of mammograms in order to identify challenging cases for each trainee. Methods: The authors’ algorithm for predicting the likelihood of missing a mass consists of three steps. First, a mammogram is segmented into air, pectoral muscle, fatty tissue, dense tissue, and mass using automated segmentation algorithms. Second, 43 features are extracted using computer vision algorithms for each abnormality identified by experts. Third, error-making models (classifiers) are applied to predict the likelihood of trainees missing the abnormality based on the extracted features. The models are developed individually for each trainee using his/her previous reading data. The authors evaluated the predictive performance of the proposed algorithm using data from a reader study in which 10 subjects (7 residents and 3 novices) and 3 experts read 100 mammographic cases. Receiver operating characteristic (ROC) methodology was applied for the evaluation. Results: The average area under the ROC curve (AUC) of the error-making models for the task of predicting which masses will be detected and which will be missed was 0.607 (95% CI,0.564-0.650). This value was statistically significantly different from 0.5 (p < 0.0001). For the 7 residents only, the AUC performance of the models was 0.590 (95% CI,0.537-0.642) and was also significantly higher than 0.5 (p = 0.0009). Therefore, generally the authors’ models were able to predict which masses were detected and which were missed better than chance. Conclusions: The authors proposed an algorithm that was able to predict which masses will be detected and which will be missed by each individual trainee. This confirms existence of error-making patterns in the detection of masses among radiology trainees. Furthermore, the proposed methodology will allow for the optimized selection of difficult cases for the trainees in an automatic and efficient manner.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

A deep learning-based Bayesian framework for high-resolution calibration of building energy models

Calibrating building energy models (BEMs), i.e., closing discrepancy between modeling and field measurements, is of significance to support its applications in building sustainability and resilience analysis. However, as being widely used in practice, current Bayesian calibration is mostly performed in low-resolution (annual or monthly), instead of high-resolution (hourly or sub-hourly), which is crucial to support emerging BEM applications, such as building-renewable energy integration (demand response) and smart control. This is attributable to the gaps in current Bayesian calibration process, including (1) difficulty in supporting reliable high-resolution calibration with over-parameterization and multi-solution issues, (2) inadequacy of meta-model to capture temporal building dynamics in high-resolution, and (3) excessive computational burdens of covariance matrix calculation in Bayesian inference. Therefore, to close these gaps, this research proposes a novel deep learning-based Bayesian calibration framework, involving pre-calibration mechanism, Long Short-Term Memory as surrogate models, and simplified covariance matrix calculation, to calibrate BEMs in high temporal resolution (i.e., hourly) with enhanced accuracy and computational efficiency. Finally, the case study demonstrates its effectiveness to match modeling outcomes with measurements and realize CV-RMSE of < 30 % and NMBE of < 6 % in hourly resolution, as well as a significant reduction of calibration time (by > 99 %, from > 600 h to ~ 1.5 h).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2002

International Conference on Remote Sensing Applications for Archaeological Research and World Heritage Conservation

Contents include the following: Monitoring the Ancient Countryside: Remote Sensing and GIS at the Chora of Chersonesos (Crimea, Ukraine). Integration of Remote Sensing and GIS for Management Decision Support in the Pendjari Biosphere Reserve (Republic of Benin). Monitoring of deforestation invasion in natural reserves of northern Madagascar based on space imagery. Cartography of Kahuzi-Biega National Park. Cartography and Land Use Change of World Heritage Areas and the Benefits of Remote Sensing and GIS for Conservation. Assessing and Monitoring Vegetation in Nabq Protected Area, South Sinai, Egypt, using combine approach of Satellite Imagery and Land Surveys. Evaluation of forage resources in semi-arid savannah environments with satellite imagery: contribution to the management of a protected area (Nakuru National Park) in Kenya. SOGHA, the Surveillance of Gorilla Habitat in World Heritage sites using Space Technologies. Application of Remote Sensing to monitor the Mont-Saint-Michel Bay (France). Application of Remote Sensing & GIS for the Conservation of Natural and Cultural Heritage Sites of the Southern Province of Sri Lanka. Social and Environmental monitoring of a UNESCO Biosphere Reserve: Case Study over the Vosges du Nord and Pfalzerwald Parks using Corona and Spot Imagery. Satellite Remote Sensing as tool to Monitor Indian Reservation in the Brazilian Amazonia. Remote Sensing and GIS Technology for Monitoring UNESCO World Heritage Sites - A Pilot Project. Urban Green Spaces: Modern Heritage. Monitoring of the technical condition of the St. Sophia Cathedral and related monastic buildings in Kiev with Space Applications, geo-positioning systems and GIS tools. The Murghab delta palaeochannel Reconstruction on the Basis of Remote Sensing from Space. Acquisition, Registration and Application of IKONOS Space Imagery for the cultural World Heritage site at Mew, Turkmenistan. Remote Sensing and VR applications for the reconstruction of archaeological landscapes. Archaeology through Space: Experience in Indian Subcontinent. The creation of a GIS Archaeological Site Location Catalogue in Yucatan: A Tool to preserve its Cultural Heritage. Mapping the Ancient Anasazi Roads of Southeast Utah. Remote Sensing and GIS Technology for Identification of Conservation and Heritage sites in Urban Planning. Mapping Angkor: For a new appraisal of the Angkor region. Angkor and radar imaging: seeing a vast pre-industrial low-density, dispersed urban complex. Technical and methodological aspects of archaeological CRM integrating high resolution satellite imagery. The contribution of satellite imagery to archaeological survey: an example from western Syria. The use of satellite images, digital elevation models and ground truth for the monitoring of land degradation in the "Cinque Terre" National park. Remote Sensing and GIS Applications for Protection and Conservation of World Heritage Site on the coast - Case Study of Tamil Nadu Coast, India. Multispectral high resolution satellite imagery in combination with "traditional" remote sensing and ground survey methods to the study of archaeological landscapes. The case study of Tuscany. Use of Remotely-Sensed Imagery in Cultural Landscape. Characterisation at Fort Hood, Texas. Heritage Learning and Data Collection: Biodiversity & Heritage Conservation through Collaborative Monitoring & Research. A collaborative project by UNESCO's WHC (World Heritage Center) & The GLOBE Program (Global Learning and Observations to Benefit the Environment). Practical Remote Sensing Activities in an Interdisciplinary Master-Level Space Course.

Source record↗

DOE OSTI2017

Parallel variable selection for effective performance prediction

Large data analysis problems often involve a large number of variables, and the corresponding analysis algorithms may examine all variable combinations to find the optimal solution. For example, to model the time required to complete a scientific workflow, we need to consider the impact of dozens of parameters. To reduce the model building time and reduce the likelihood of overfitting, we look to variable selection methods to identify the critical variables for the performance model. In this work, we create a combination of variable selection and performance prediction methods that is as effective as the exhaustive search approach when the exhaustive search could be completed in a reasonable amount of time. To handle the cases where the exhaustive search is too time consuming, we develop the parallelized variable selection algorithm. Additionally, we develop a parallel grouping mechanism that further reduces the variable selection time by 70%.As a case study, we exercise the variable selection technique with the performance measurement data from the Palomar Transient Factory (PTF) workflow. The application scientists have determined that about 50 variables and parameters are important to the performance of the workflows. Our tests show that the Sequential Backward Selection algorithm is able to approximate the optimal subset relatively quickly. By reducing the number of variables used to build the model from 50 to 4, we are able to maintain the prediction quality while reducing the model building time by a factor of 6. Using the parallelization and grouping techniques we developed in this work, the variable selection process was reduced from over 18 hours to 15 minutes while ending up with the same variable subset.

Wang, J↗

DOE OSTI2017

Case Study for the ARRA-funded GSHP Demonstration at Furman University

With funding provided by the American Recovery and Reinvestment Act, 26 ground source heat pump (GSHP) projects were competitively selected in 2009 to demonstrate the benefits of GSHP systems and innovative technologies for cost reduction and/or performance improvement. One of the selected demonstration projects was proposed by Furman University for ten student housing buildings—the North Village located on the campus in Greeneville, South Carolina. All ten buildings are identical in floor plan and construction. Each building is conditioned by an identical GSHP system consisting of 25 water-to-air heat pump (WAHP) units, a closed-loop vertical ground heat exchanger (GHX) installed under an adjacent parking lot, and two redundant 7.5 hp variable-speed pumps to circulate water through the GHX and the WAHPs. The actual performance of the GSHP systems is analyzed with available measured data for 2014. The annual energy performance is compared with a baseline scenario in which the building is conditioned by air-source heat pumps (ASHPs) with the minimum allowed efficiencies specified in ASHRAE Standard 90.1-2013 (SEER 13 for cooling and 7.8 HSPF for heating) and supplemental electric heaters. The comparison is made in terms of energy savings, operating cost savings, cost-effectiveness, and environmental benefits. Finally, limitations in conducting this analysis are identified and recommendations for further improving the operational efficiency of the GSHP systems are made.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2014

Existing Whole-House Case Study: Evaluation of Missed Energy Saving Opportunity Based on Illinois Home Performance Program Field Data: Homeowner Selected Upgrades vs. Cost-Optimized Solutions, Chicago, Illinois

Expanding on previous research by PARR, this study compares measure packages installed during 800 Illinois Home Performance with ENERGY STAR® (IHP) residential retrofits to those recommended as cost-optimal by Building Energy Optimization (BEopt) modeling software. In previous research, cost-optimal measure packages were identified for 15 Chicagoland single family housing archetypes, called housing groups. In the present study, 800 IHP homes are first matched to one of these 15 housing groups, and then the average measures being installed in each housing group are modeled using BEopt to estimate energy savings. For most housing groups, the differences between recommended and installed measure packages is substantial. By comparing actual IHP retrofit measures to BEopt-recommended cost-optimal measures, missed savings opportunities are identified in some housing groups; also, valuable information is obtained regarding housing groups where IHP achieves greater savings than BEopt-modeled, cost-optimal recommendations.

Air Sealing↗