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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Network and User-Perceived Performance of Web Page Retrievals

The development of the HTTP protocol has been driven by the need to improve the network performance of the protocol by allowing the efficient retrieval of multiple parts of a web page without the need for multiple simultaneous TCP connections between a client and a server. We suggest that the retrieval of multiple page elements sequentially over a single TCP connection may result in a degradation of the perceived performance experienced by the user. We attempt to quantify this perceived degradation through the use of a model which combines a web retrieval simulation and an analytical model of TCP operation. Starting with the current HTTP/l.1 specification, we first suggest a client@side heuristic to improve the perceived transfer performance. We show that the perceived speed of the page retrieval can be increased without sacrificing data transfer efficiency. We then propose a new client/server extension to the HTTP/l.1 protocol to allow for the interleaving of page element retrievals. We finally address the issue of the display of advertisements on web pages, and in particular suggest a number of mechanisms which can make efficient use of IP multicast to send advertisements to a number of clients within the same network.

Kruse, Hans↗
NASA NTRS2011

Data Mining of Network Logs

The statement of purpose is to analyze network monitoring logs to support the computer incident response team. Specifically, gain a clear understanding of the Uniform Resource Locator (URL) and its structure, and provide a way to breakdown a URL based on protocol, host name domain name, path, and other attributes. Finally, provide a method to perform data reduction by identifying the different types of advertisements shown on a webpage for incident data analysis. The procedures used for analysis and data reduction will be a computer program which would analyze the URL and identify and advertisement links from the actual content links.

Collazo, Carlimar↗
DOE OSTI2011

Integrating semantic web technologies and geospatial catalog services for geospatial information discovery and processing in cyberinfrastructure

Abstract A geospatial catalogue service provides a network-based meta-information repository and interface for advertising and discovering shared geospatial data and services. Descriptive information (i.e., metadata) for geospatial data and services is structured and organized in catalogue services. The approaches currently available for searching and using that information are often inadequate. Semantic Web technologies show promise for better discovery methods by exploiting the underlying semantics. Such development needs special attention from the Cyberinfrastructure perspective, so that the traditional focus on discovery of and access to geospatial data can be expanded to support the increased demand for processing of geospatial information and discovery of knowledge. Semantic descriptions for geospatial data, services, and geoprocessing service chains are structured, organized, and registered through extending elements in the ebXML Registry Information Model (ebRIM) of a geospatial catalogue service, which follows the interface specifications of the Open Geospatial Consortium (OGC) Catalogue Services for the Web (CSW). The process models for geoprocessing service chains, as a type of geospatial knowledge, are captured, registered, and discoverable. Semantics-enhanced discovery for geospatial data, services/service chains, and process models is described. Semantic search middleware that can support virtual data product materialization is developed for the geospatial catalogue service. The creation of such a semantics-enhanced geospatial catalogue service is important in meeting the demands for geospatial information discovery and analysis in Cyberinfrastructure.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2011

Mobile phone collection, reuse and recycling in the UK

Highlights: > We characterized the key features of the voluntary UK mobile phone takeback network via a survey. > We identified 3 flows: information; product (handsets and accessories); and incentives. > There has been a significant rise in the number of UK takeback schemes since 1997. > Most returned handsets are low quality; little data exists on quantities of mobile phones collected. > Takeback schemes increasingly divert EoL mobile phones from landfill and enable reuse/recycling. - Abstract: Mobile phones are the most ubiquitous electronic product on the globe. They have relatively short lifecycles and because of their (perceived) in-built obsolescence, discarded mobile phones represent a significant and growing problem with respect to waste electrical and electronic equipment (WEEE). An emerging and increasingly important issue for industry is the shortage of key metals, especially the types of metals found in mobile phones, and hence the primary aim of this timely study was to assess and evaluate the voluntary mobile phone takeback network in the UK. The study has characterised the information, product and incentives flows in the voluntary UK mobile phone takeback network and reviewed the merits and demerits of the incentives offered. A survey of the activities of the voluntary mobile phone takeback schemes was undertaken in 2008 to: identify and evaluate the takeback schemes operating in the UK; determine the target groups from whom handsets are collected; and assess the collection, promotion and advertising methods used by the schemes. In addition, the survey sought to identify and critically evaluate the incentives offered by the takeback schemes, evaluate their ease and convenience of use; and determine the types, qualities and quantities of mobile phones they collect. The study has established that the UK voluntary mobile phone takeback network can be characterised as three distinctive flows: information flow; product flow (handsets and related accessories); and incentives flow. Over 100 voluntary schemes offering online takeback of mobile phone handsets were identified. The schemes are operated by manufacturers, retailers, mobile phone network service operators, charities and by mobile phone reuse, recycling and refurbishing companies. The latter two scheme categories offer the highest level of convenience and ease of use to their customers. Approximately 83% of the schemes are either for-profit/commercial-oriented and/or operate to raise funds for charities. The voluntary schemes use various methods to collect mobile phones from consumers, including postal services, courier and in-store. The majority of schemes utilise and finance pre-paid postage to collect handsets. Incentives offered by the takeback schemes include monetary payments, donation to charity and entry into prize draws. Consumers from whom handsets and related equipment are collected include individuals, businesses, schools, colleges, universities, charities and clubs with some schemes specialising on collecting handsets from one target group. The majority (84.3%) of voluntary schemes did not provide information on their websites about the quantities of mobile phones they collect. The operations of UK takeback schemes are decentralised in nature. Comparisons are made between the UK's decentralised collection system versus Australia's centralised network for collection of mobile phones. The significant principal conclusions from the study are: there has been a significant rise in the number of takeback schemes operating in the UK since the initial scheme was launched in 1997; the majority of returned handsets seem to be of low quality; and there is very little available information on the quantities of mobile phones collected by the various schemes. Irrespective of their financial motives, UK takeback schemes increasingly play an important role in sustainable waste management by diverting EoL mobile phones from landfills and encouraging reuse and recycling. Recommendations for future actions to improve the management of end-of-life mobile phone handsets and related accessories are made.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

What do we mean by the word “Shock”?

From one vantage point, a shock is a continuous but drastic change in state variables that occurs over very small time and length scales. These scales and associated changes in state variables can be measured experimentally. From another vantage point, a shock is a mathematical singularity consisting of instantaneous changes in state variables. This more mathematical view gives rise to analytical solutions to idealized problems. And from a third vantage point, a shock is a structure in a hydrocode prediction. Its width depends on the simulation’s grid resolution and artificial viscosity. These three vantage points can be in conflict when ideas from the associated fields are combined, and yet combining them is an important goal of an integrated modeling program. This presentation explores an example of how models for real materials in the presence of real shocks react to a hydrocode’s numerical shocks of finite width. The presentation will include an introduction to plasticity for the novice, an historical view of plasticity algorithms, a demonstration of how pursuing the meaning of “shock” has resulted in hydrocode improvements, and will conclude by answering some of the questions that arise from that pursuit. After the technical part of the presentation, a few slides advertising LANL’s Computational Physics Student Summer Workshop will be shown.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Tell your sustainability story, minus hype

Monthly Economic Diversication column for the Tri-City Herald... By now, many of us are starting to slack off on our New Year’s resolutions to vigorously become healthier, happier, more productive superhumans. While our intentions are in the right place, we try to insert these lofty goals into already hectic lives wrought with engrained routines. We break them because they’re simply not sustainable unless they become integral to our daily operation. The same is true of businesses who still think going "green" is something to talk about rather than wholeheartedly do. The concept of being "green" started as a buzzword several years ago, something companies would attach to their advertising to convince customers they cared about more than just making a buck. Since that time, the concept now referred to as "sustainability" has evolved considerably and is becoming a fundamental part of how companies do business. As such, marketing efforts to tout sustainability, previously seen as fluffy, are now respected for their proven power to affect the bottom line.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Business Solutions Case Study: Marketing Zero Energy Homes: Tommy Williams Homes, Gainesville, Florida

Building America research has shown that high-performance homes can potentially give builders an edge in the marketplace and can boost sales, but it doesn't happen automatically. It requires a tailored, easy-to-understand marketing campaign, and sometimes a little flair. This case study highlights the successful marketing approach of Tommy Williams Homes, which devotes resources to advertising, targeted social media outlets and blogs, realtor education seminars, and groundbreaking and open house celebrations. As a result, in one community, 2013 property sales records show that TWH outsells the only other builder in the development at a higher price, with fewer days on the market.

Advertising↗
DOE OSTI2015

Business Solutions Case Study: Marketing Zero Energy Homes: LifeStyle Homes, Melbourne, Florida

Building America research has shown that high-performance homes can potentially give builders an edge in the marketplace and can boost sales. But it doesn't happen automatically. It requires a tailored, easy to understand marketing campaign and sometimes a little flair. This case study highlights LifeStyle Homes’ successful marketing approach for their SunSmart home package, which has helped to boost sales for the company. SunSmart marketing includes a modified logo, weekly blog, social media, traditional advertising, website, and sales staff training. Marketing focuses on quality, durability, healthy indoor air, and energy efficiency with an emphasis on the surety of third-party verification and the scientific approach to developing the SunSmart package. With the introduction of SunSmart, LifeStyle began an early recovery, nearly doubling sales in 2010; SunSmart sales now exceed 300 homes, including more than 20 zero energy homes. Completed homes in 2014 far outpaced the national (19%) and southern census region (27%) recovery rates for the same period. As technology improves and evolves, this builder will continue to collaborate with Building America.

Advertising↗
DOE OSTI2025

What Is a Polyolefin? A Critical Overview of Ethylene Copolymers Used as Solar Photovoltaic Module Encapsulants

In recent years, photovoltaic (PV) encapsulant films marketed as polyolefins (POs), more specifically as PO elastomers (POEs) and thermoplastic POs (TPOs), have gained significant market share and are projected to become the dominant encapsulation films by 2030. Relative to other industries, there are significant misconceptions about the term PO in the PV industry. Both in the scientific literature as well as in sales and advertising, the terms PO, POE, and TPO are often misused to describe the same type of material with comparable properties, while in reality these may each consist of separate material classes. This paper provides a comprehensive literature and market review, to showcase a broad range of PO and other ethylene copolymer encapsulants from recent studies, and discusses the materials' properties to clarify what constitutes a “polyolefin.” In addition, to promote a clearer comparison of encapsulant properties, we propose a two‐dimensional taxonomy to categorize polymers used in module manufacturing, including POs. In terms of improving the reliability of solar PV modules, PO‐based encapsulants have several advantages (including lower water uptake and ion diffusion), but might come with disadvantages too, such as a more complex processing and a higher sensitivity to the storage conditions and shelf life. All this might prospectively impact adhesion properties of the encapsulant to other materials' interfaces (glass, cells etc.) and end‐product quality. Because the track record of field‐deployed PV modules containing PO encapsulants is also limited, we hope to contribute to better material understanding and precision in communication in PV to secure quality.

14 SOLAR ENERGY↗
DOE OSTI2016

Clustering VoIP caller for SPIT identification

Abstract The number of unsolicited and advertisement telephony calls over traditional and Internet telephony has rapidly increased over recent few years. Every year, the telecommunication regulators, law enforcement agencies and telecommunication operators receive a very large number of complaints against these unsolicited, unwanted calls. These unwanted calls not only bring financial loss to the users of the telephony but also annoy them with unwanted ringing alerts. Therefore, it is important for the operators to block telephony spammers at the edge of the network so to gain trust of their customers. In this paper, we propose a novel spam detection system by incorporating different social network features for combating unwanted callers at the edge of the network. To this extent the reputation of each caller is computed by processing call detailed records of user using three social network features that are the frequency of the calls between caller and the callee, the duration between caller and the callee and the number of outgoing partners associated with the caller. Once the reputation of the caller is computed, the caller is then places in a spam and non‐spam clusters using unsupervised machine learning. The performance of the proposed approach is evaluated using a synthetic dataset generated by simulating the social behaviour of the spammers and the non‐spammers. The evaluation results reveal that the proposed approach is highly effective in blocking spammer with 2% false positive rate under a large number of spammers. Moreover, the proposed approach does not require any change in the underlying VoIP network architecture, and also does not introduce any additional signalling delay in a call set‐up phase. Copyright © 2016 John Wiley & Sons, Ltd.

Azad, Muhammad Ajmal↗
DOE OSTI2018

Stellarator Research Opportunities: A Report of the National Stellarator Coordinating Committee

This paper is the product of a stellarator community workshop, organized by the National Stellarator Coordinating Committee and referred to as Stellcon, that was held in Cambridge, Massachusetts in February 2016, hosted by MIT. The workshop was widely advertised, and was attended by 40 scientists from 12 different institutions including national labs, universities and private industry, as well as a representative from the Department of Energy. The final section of this document describes areas of community wide consensus that were developed as a result of the discussions held at that workshop. Areas where further study would be helpful to generate a consensus path forward for the US stellarator program are also discussed. The program outlined in this document is directly responsive to many of the strategic priorities of FES as articulated in “Fusion Energy Sciences: A Ten-Year Perspective (2015–2025)” [1]. The natural disruption immunity of the stellarator directly addresses “Elimination of transient events that can be deleterious to toroidal fusion plasma confinement devices” an area of critical importance for the US fusion energy sciences enterprise over the next decade. Another critical area of research “Strengthening our partnerships with international research facilities,” is being significantly advanced on the W7-X stellarator in Germany and serves as a test-bed for development of successful international collaboration on ITER. Finally, this report also outlines how materials science as it relates to plasma and fusion sciences, another critical research area, can be carried out effectively in a stellarator. Additionally, significant advances along two of the Research Directions outlined in the report; “Burning Plasma Science: Foundations—Next-generation research capabilities”, and “Burning Plasma Science: Long pulse—Sustainment of Long-Pulse Plasma Equilibria” are proposed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Residential retrofits at scale: opportunity identification, saving estimation, and personalized messaging based on communicating thermostat data

Basic insulation and heating system retrofits of existing homes could achieve annual energy savings of up to $4–5 billion in the USA. However, current US utility energy efficiency (EE) programs are costly and challenging to scale. Customer acquisition occurs primarily through energy bill mailers, mass media, and on-line advertising that lack specificity about particular home retrofit opportunities, expected energy savings, and cost-effectiveness. Specific retrofit opportunities are identified via on-site home energy assessments that can be inconvenient to homeowners, expensive, and of variable accuracy. Our paper discusses using communicating thermostat data to significantly increase the customer uptake of energy conservation measures (ECMs) by identifying homes with the most significant retrofit opportunities, estimating post-retrofit energy savings, and formulating home-specific outreach. We extended our previously developed gray-box building model to identify physical building parameters corresponding to the target retrofit opportunities, i.e., whole-home R value, air leakage characteristics, and heating system efficiency. Here, the estimated R values and air leakage characteristics compare favorably with the ground truth. The validated algorithms can calculate home-specific energy savings estimate for each ECM, and the algorithm outputs can be used by utility EE programs to formulate home-specific retrofit offers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Molecular Communication over Gas Stream Channels using Portable Mass Spectrometry

The synthetic generation/coding and transmission of olfactory information over a gas stream or an odor network is a new and unexplored field. Application areas vary from the entertainment or advertisement industry to security and telemedicine. However, current technological limitations frustrate the accurate reproduction of decoded and transmitted olfactory data. This study describes the development, testing, and characterization of a novel odor emitter (OE) that is used to investigate the generation-encoding of gaseous standards with odorous characteristics with a regulatable way, for scent transmission purposes. The calibration and the responses of a developed OE were examined using a portable quadrupole mass spectrometer (MS). Experiments were undertaken for a range of volatile organic compounds (VOCs) at different temperatures and flow rates. Individual compounds and mixtures were tested to investigate periodic and dynamic transmission characteristics within two different size tubular containers for distances up to 3 m. Olfactory information transmission is demonstrated using MS as the main molecular sensor for odor detection and monitoring and for the first time spatial encryption of olfactory information is shown. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Inverse reinforcement learning control for building energy management

Reinforcement learning (RL) based control is widely considered a promising approach in building automation and control as it has demonstrated the potential to deal with complex objectives in adjacent domains like robotics, autonomous vehicles, gaming applications, and advertisement recommendations. When applied to any environment, model-free RL learns to improve its control performance over time without requiring a control model, by receiving and then analyzing feedback from the building environment after each control action. Operational objectives are becoming increasingly complex through the simultaneous consideration of thermal comfort, carbon emissions, grid services, and indoor air quality. In this context, conventional rule-based control approaches are proving sub-optimal, mostly heuristic, and inadequate. The model-free and self learning nature of RL appears promising and attractive as it may address the scalability issues associated with advanced control approaches. However, it suffers from long training times and unstable control behavior during the early stages of its learning process, which makes it unsuitable to be applied directly to buildings. This paper addresses these issues using an inverse reinforcement learning approach (IRL), a technique utilized to learn the objective of a controller agent which is considered an expert in its respective domain. Here, we consider a rule-based control as the expert demonstrator. IRL is different from a direct imitation (i.e., direct mapping of states to actions) of control actions as it tries to find the underlying intent of an expert's policy, providing the controller with a better-generalized policy for unseen states or environments with slightly different dynamics. This approach propels the RL controller's policy to levels similar to or better than that of a rule-based policy before it starts learning by interacting with the building. This makes RL for building energy management applications more practical as it prevents the erratic and exploratory behavior in the initial training period, simultaneously speeding up the learning process when compared to applying an untrained RL agent directly to a building environment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Scaling Deep Learning workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing

Deep Learning (DL) algorithms have become ubiquitous in data analytics. As a result, major computing vendors—including NVIDIA, Intel, AMD, and IBM—have architectural road maps influenced by DL workloads. Furthermore, several vendors have recently advertised new computing products as accelerating large DL workloads. Unfortunately, it is difficult for data scientists to quantify the potential of these different products. Here, this article provides a performance and power analysis of important DL workloads on two major parallel architectures: NVIDIA DGX-1 (eight Pascal P100 GPUs interconnected with NVLink) and Intel Knights Landing (KNL) CPUs interconnected with Intel Omni-Path or Cray Aries. Our evaluation consists of a cross section of convolutional neural net workloads: CifarNet, AlexNet, GoogLeNet, and ResNet50 topologies using the Cifar10 and ImageNet datasets. The workloads are vendor-optimized for each architecture. We use sequentially equivalent implementations to maintain iso-accuracy between parallel and sequential DL models. Our analysis indicates that although GPUs provide the highest overall performance, the gap can close for some convolutional networks; and the KNL can be competitive in performance/watt. We find that NVLink facilitates scaling efficiency on GPUs. However, its importance is heavily dependent on neural network architecture. Furthermore, for weak-scaling—sometimes encouraged by restricted GPU memory—NVLink is less important.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Machine Learning Approaches for Predicting Radiation Therapy Outcomes: A Clinician's Perspective

Radiation oncology has always been deeply rooted in modeling, from the early days of isoeffect curves to the contemporary Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) initiative. In recent years, medical modeling for both prognostic and therapeutic purposes has exploded thanks to increasing availability of electronic data and genomics. One promising direction that medical modeling is moving toward is adopting the same machine learning methods used by companies such as Google and Facebook to combat disease. Broadly defined, machine learning is a branch of computer science that deals with making predictions from complex data through statistical models. These methods serve to uncover patterns in data and are actively used in areas such as speech recognition, handwriting recognition, face recognition, “spam” filtering (junk email), and targeted advertising. Although multiple radiation oncology research groups have shown the value of applied machine learning (ML), clinical adoption has been slow due to the high barrier to understanding these complex models by clinicians. Here, we present a review of the use of ML to predict radiation therapy outcomes from the clinician's point of view with the hope that it lowers the “barrier to entry” for those without formal training in ML. We begin by describing 7 principles that one should consider when evaluating (or creating) an ML model in radiation oncology. We next introduce 3 popular ML methods—logistic regression (LR), support vector machine (SVM), and artificial neural network (ANN)—and critique 3 seminal papers in the context of these principles. Although current studies are in exploratory stages, the overall methodology has progressively matured, and the field is ready for larger-scale further investigation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2011

Energy-Charge-conserving, Implicit, Electrostatic Particle-in-Cell Algorithm

This paper discusses a novel fully implicit formulation for a one-dimensional electrostatic particle-in-cell (PIC) plasma simulation approach. Unlike earlier implicit electrostatic PIC approaches (which are based on a linearized Vlasov-Poisson formulation), ours is based on a nonlinearly converged Vlasov-Ampere (VA) model. By iterating particles and fields to a tight nonlinear convergence tolerance, the approach features superior stability and accuracy properties, avoiding most of the accuracy pitfalls in earlier implicit PIC implementations. In particular, the formulation is stable against temporal (Courant-Friedrichs-Lewy) and spatial (aliasing) instabilities. It is charge- and energy-conserving to numerical round-off for arbitrary implicit time steps (unlike the earlier ''energy-conserving'' explicit PIC formulation, which only conserves energy in the limit of arbitrarily small time steps). While momentum is not exactly conserved, errors are kept small by an adaptive particle sub-stepping orbit integrator, which is instrumental to prevent particle tunneling (a deleterious effect for long-term accuracy). The VA model is orbit-averaged along particle orbits to enforce an energy conservation theorem with particle sub-stepping. As a result, very large time steps, constrained only by the dynamical time scale of interest, are possible without accuracy loss. Algorithmically, the approach features a Jacobian-free Newton-Krylov solver. A main development in this study is the nonlinear elimination of the new-time particle variables (positions and velocities). Such nonlinear elimination, which we term particle enslavement, results in a nonlinear formulation with memory requirements comparable to those of a fluid computation, and affords us substantial freedom in regards to the particle orbit integrator. Numerical examples are presented that demonstrate the advertised properties of the scheme. In particular, long-time ion acoustic wave simulations show that numerical accuracy does not degrade even with very large implicit time steps, and that significant CPU gains are possible.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗