Download or read book Energy Dependent Bias in the Weighted Point Model written by and published by . This book was released on 2005 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: While the weighted point multiplicity model has successfully reduced the bias that is associated with variable multiplication of neutrons within a sample (which was assumed constant in the standard point multiplicity model), other potential sources of bias still exists within the weighted point model. One significant source of bias arises from the assumption that the energies of the neutrons from ([alpha], n) reactions on impurities in the sample have the same average energy as neutrons emitted from the spontaneous fission of 24°Pu. An investigation into the effects that neutron energy has on the assay results (effective 24°Pu mass, alpha, and multiplication) of the weighted point multiplicity model has been performed using MCNPX, Version 2.5f for impure plutonium metal samples in a number of different detector systems. The effects of energy dependence of the detection efficiency and gate fractions on the assay results, as well as the measured singles, doubles, and triples rates were also studied. Methods for mitigating the effects of neutron energy on the weighted-point multiplicity model results will be presented and discussed.
Download or read book Reduction of Bias in Neutron Multiplicity Assay Using a Weighted Point Model written by and published by . This book was released on 2004 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate assay of most common plutonium samples was the development goal for the nondestructive assay technique of neutron multiplicity counting. Over the past 20 years the technique has been proven for relatively pure oxides and small metal items. Unfortunately, the technique results in large biases when assaying large metal items. Limiting assumptions, such as unifoh multiplication, in the point model used to derive the multiplicity equations causes these biases for large dense items. A weighted point model has been developed to overcome some of the limitations in the standard point model. Weighting factors are detemiined from Monte Carlo calculations using the MCNPX code. Monte Carlo calculations give the dependence of the weighting factors on sample mass and geometry, and simulated assays using Monte Carlo give the theoretical accuracy of the weighted-point-model assay. Measured multiplicity data evaluated with both the standard and weighted point models are compared to reference values to give the experimental accuracy of the assay. Initial results show significant promise for the weighted point model in reducing or eliminating biases in the neutron multiplicity assay of metal items. The negative biases observed in the assay of plutonium metal samples are caused by variations in the neutron multiplication for neutrons originating in various locations in the sample. The bias depends on the mass and shape of the sample and depends on the amount and energy distribution of the ([alpha], n) neutrons in the sample. When the standard point model is used, this variable-multiplication bias overestimates the multiplication and alpha values of the sample, and underestimates the plutonium mass. The weighted point model potentially can provide assay accuracy of H"% (1 [sigma]) for cylindrical plutonium metal samples
Download or read book Model dependent and Design dependent Sampling Procedures written by Hans T. Schreuder and published by . This book was released on 1990 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nuclear Science Abstracts written by and published by . This book was released on 1974 with total page 1174 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Internal Photoemission Spectroscopy written by Valeri V. Afanas'ev and published by Elsevier. This book was released on 2010-07-07 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: The monographic book addresses the basics of the charge carrier photoemission from one solid to another - the internal photoemission, (IPE) - and different spectroscopic applications of this phenomenon to solid state heterojunctions. This is the first book in the field of IPE, which complements the conventional external photoemission spectroscopy by analysing interfaces separated from the sample surface by a layer of a different solid or liquid. IPE is providing the most straightforward and, therefore, reliable information regarding the energy spectrum of electron states at interfaces. At the same time, the method provides the unique capability of analysing the heterostructures relevant to the modern micro- and nano-electronic devices as well as new materials involved in their design and fabrication.In addition to the discussion of fundamental physical and technical aspects of IPE spectroscopic applications, several "hot topics are addressed. These include development of new insulating materials for advances Si MOS technology (both high-k gate insulators and low-k dielectrics for interconnect insulation), metal gate materials, development of heterostructures based on high-mobility semiconductors, etc. Thanks to a considerable activity in this field over the last few years, the recent results concerning band structure of most important interfaces involving novel materials can now be documented.- First complete description of the internal photoemission phenomena - A practical guide to internal photoemission measurements- Describes reliable energy barrier determination procedures - Surveys trap spectroscopy methods applicable to thin insulating layers- Provides an overview of the most recent results on band structure of high-permittivity insulating materials and their interfaces- Contains a complete collection of reference data on interface band alignment for wide-bandgap insulating materials in contact with metals and semiconductors
Download or read book 1995 URSI International Symposium on Signals Systems and Electronics written by and published by Institute of Electrical & Electronics Engineers(IEEE). This book was released on 1995 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Power Knowledge and Politics written by John A. Hird and published by Georgetown University Press. This book was released on 2005-03-29 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: If knowledge is power, then John Hird has opened the doors for anyone interested in public policymaking and policy analysis on the state level. A beginning question might be: does politics put gasoline or sugar in the tank? More specifically, in a highly partisan political environment, is nonpartisan expertise useful to policymaking? Do policy analysts play a meaningful role in decision making? Does policy expertise promote democratic decision making? Does it vest power in an unelected and unaccountable elite, or does it become co-opted by political actors and circumstances? Is it used to make substantive changes or just for window-dressing? In a unique comparative focus on state policy, Power, Knowledge, and Politics dissects the nature of the policy institutions that policymakers establish and analyzes the connection between policy research and how it is actually used in decision making. Hird probes the effects of politics and political institutions—parties, state political culture and dynamics, legislative and gubernatorial staffing, partisan think tanks, interest groups—on the nature and conduct of nonpartisan policy analysis. Through a comparative examination of institutions and testing theories of the use of policy analysis, Hird draws conclusions that are more useful than those derived from single cases. Hird examines nonpartisan policy research organizations established by and operating in U.S. state legislatures—one of the most intense of political environments—to determine whether and how nonpartisan policy research can survive in that harsh climate. By first detailing how nonpartisan policy analysis organizations came to be and what they do, and then determining what state legislators want from them, he presents a rigorous statistical analysis of those agencies in all 50 states and from a survey of 800 state legislators. This thoroughly comprehensive look at policymaking at the state level concludes that nonpartisan policy analysis institutions can play an important role—as long as they remain scrupulously nonpartisan.
Download or read book Low Carbon Oriented Improvement Strategy for Flexibility and Resiliency of Multi Energy Systems written by Yumin Zhang and published by Frontiers Media SA. This book was released on 2024-09-18 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the inherent volatility and randomness, the increasing share of energy from renewable resources presents a challenge to the operation of multi-energy systems with heterogeneous energy carriers such as electricity, heat, hydrogen, etc. These factors will make the systems hard to adjust their supply and demand flexibly to maintain energy balance to ensure reliability. Further, this hinders the development of a low-carbon and economically viable energy system. By making full use of the synergistic interaction of generation, transmission, load demand, and energy storage, a three-fold approach focused on quantifying demand flexibility, evaluating supply capabilities, and enhancing resilience can unlock the flexibility potential across various sectors of new energy systems. This approach provides an effective means of facilitating the transition from conventional energy systems to low-carbon, clean-energy-oriented paradigms. However, huge challenges arising from renewable energy pose great obstacles to the aforementioned solution pathway. The main objectives of this Research Topic are： 1. Develop advanced carbon emission accounting and measurement techniques for emerging multi-energy systems 2. Design effective methods for predicting renewable electricity generation 3. Proposed efficient methods for quantitative assessment of uncertainty from renewables and loads 4. Put forward advanced evaluation, optimization, and planning strategies incorporating diverse flexibility resources 5. Design multifaceted market mechanisms and collaborative frameworks balancing economics and low carbon footprint 6. Develop operational control and resilience-enhancement techniques for distribution networks under large-scale distributed energy integration
Download or read book Nanoscience and Engineering in Superconductivity written by Victor Moshchalkov and published by Springer Science & Business Media. This book was released on 2010-11-10 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: For emerging energy saving technologies superconducting materials with superior performance are needed. Such materials can be developed by manipulating the "elementary building blocks" through nanostructuring. For superconductivity the "elementary blocks" are Cooper pair and fluxon (vortex). This book presents new ways how to modify superconductivity and vortex matter through nanostructuring and the use of nanoscale magnetic templates. The basic nano-effects, vortex and vortex-antivortex patterns, vortex dynamics, Josephson phenomena, critical currents, and interplay between superconductivity and ferromagnetism at the nanoscale are discussed. Potential applications of nanostructured superconductors are also presented in the book.
Download or read book Discovery in Physics written by Katharina Morik and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-12-31 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is part of Artificial Intelligence since its beginning. Certainly, not learning would only allow the perfect being to show intelligent behavior. All others, be it humans or machines, need to learn in order to enhance their capabilities. In the eighties of the last century, learning from examples and modeling human learning strategies have been investigated in concert. The formal statistical basis of many learning methods has been put forward later on and is still an integral part of machine learning. Neural networks have always been in the toolbox of methods. Integrating all the pre-processing, exploitation of kernel functions, and transformation steps of a machine learning process into the architecture of a deep neural network increased the performance of this model type considerably. Modern machine learning is challenged on the one hand by the amount of data and on the other hand by the demand of real-time inference. This leads to an interest in computing architectures and modern processors. For a long time, the machine learning research could take the von-Neumann architecture for granted. All algorithms were designed for the classical CPU. Issues of implementation on a particular architecture have been ignored. This is no longer possible. The time for independently investigating machine learning and computational architecture is over. Computing architecture has experienced a similarly rampant development from mainframe or personal computers in the last century to now very large compute clusters on the one hand and ubiquitous computing of embedded systems in the Internet of Things on the other hand. Cyber-physical systems’ sensors produce a huge amount of streaming data which need to be stored and analyzed. Their actuators need to react in real-time. This clearly establishes a close connection with machine learning. Cyber-physical systems and systems in the Internet of Things consist of diverse components, heterogeneous both in hard- and software. Modern multi-core systems, graphic processors, memory technologies and hardware-software codesign offer opportunities for better implementations of machine learning models. Machine learning and embedded systems together now form a field of research which tackles leading edge problems in machine learning, algorithm engineering, and embedded systems. Machine learning today needs to make the resource demands of learning and inference meet the resource constraints of used computer architecture and platforms. A large variety of algorithms for the same learning method and, moreover, diverse implementations of an algorithm for particular computing architectures optimize learning with respect to resource efficiency while keeping some guarantees of accuracy. The trade-off between a decreased energy consumption and an increased error rate, to just give an example, needs to be theoretically shown for training a model and the model inference. Pruning and quantization are ways of reducing the resource requirements by either compressing or approximating the model. In addition to memory and energy consumption, timeliness is an important issue, since many embedded systems are integrated into large products that interact with the physical world. If the results are delivered too late, they may have become useless. As a result, real-time guarantees are needed for such systems. To efficiently utilize the available resources, e.g., processing power, memory, and accelerators, with respect to response time, energy consumption, and power dissipation, different scheduling algorithms and resource management strategies need to be developed. This book series addresses machine learning under resource constraints as well as the application of the described methods in various domains of science and engineering. Turning big data into smart data requires many steps of data analysis: methods for extracting and selecting features, filtering and cleaning the data, joining heterogeneous sources, aggregating the data, and learning predictions need to scale up. The algorithms are challenged on the one hand by high-throughput data, gigantic data sets like in astrophysics, on the other hand by high dimensions like in genetic data. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Novel machine learning algorithms are optimized with regard to minimal resource consumption. Moreover, learned predictions are applied to program executions in order to save resources. The three books will have the following subtopics: Volume 1: Machine Learning under Resource Constraints - Fundamentals Volume 2: Machine Learning and Physics under Resource Constraints - Discovery Volume 3: Machine Learning under Resource Constraints - Applications Volume 2 is about machine learning for knowledge discovery in particle and astroparticle physics. Their instruments, e.g., particle accelerators or telescopes, gather petabytes of data. Here, machine learning is necessary not only to process the vast amounts of data and to detect the relevant examples efficiently, but also as part of the knowledge discovery process itself. The physical knowledge is encoded in simulations that are used to train the machine learning models. At the same time, the interpretation of the learned models serves to expand the physical knowledge. This results in a cycle of theory enhancement supported by machine learning.
Download or read book The Second Compton Symposium written by N. Gehrels and published by American Inst. of Physics. This book was released on 1998-03-19 with total page 824 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation Proceedings of a conference held in College Park, Maryland, in September 1993. Papers discuss results from the Compton Gamma Ray Observatory, in orbit since 1991. Presentations are divided into sections on opening remarks, spin-powered pulsars, nucleosynthesis, galactic sources, galactic center, cosmic rays and galactic diffusion radiation, agn-seyferts, agn-quasars and bl lacs, and analysis and instrumentation. No index. Annotation c. by Book News, Inc., Portland, Or.
Download or read book General Relativity and Gravitation written by Abhay Ashtekar and published by Cambridge University Press. This book was released on 2015-06-01 with total page 697 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore spectacular advances in cosmology, relativistic astrophysics, gravitational wave science, mathematics, computational science, and the interface of gravitation and quantum physics with this unique celebration of the centennial of Einstein's discovery of general relativity. Twelve comprehensive and in-depth reviews, written by a team of world-leading international experts, together present an up-to-date overview of key topics at the frontiers of these areas, with particular emphasis on the significant developments of the last three decades. Interconnections with other fields of research are also highlighted, making this an invaluable resource for both new and experienced researchers. Commissioned by the International Society on General Relativity and Gravitation, and including accessible introductions to cutting-edge topics, ample references to original research papers, and informative colour figures, this is a definitive reference for researchers and graduate students in cosmology, relativity, and gravitational science.
Download or read book Geographically Weighted Regression written by A. Stewart Fotheringham and published by John Wiley & Sons. This book was released on 2003-02-21 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geographical Weighted Regression (GWR) is a new local modelling technique for analysing spatial analysis. This technique allows local as opposed to global models of relationships to be measured and mapped. This is the first and only book on this technique, offering comprehensive coverage on this new 'hot' topic in spatial analysis. * Provides step-by-step examples of how to use the GWR model using data sets and examples on issues such as house price determinants, educational attainment levels and school performance statistics * Contains a broad discussion of and basic concepts on GWR through to ideas on statistical inference for GWR models * uniquely features accompanying author-written software that allows users to undertake sophisticated and complex forms of GWR within a user-friendly, Windows-based, front-end (see book for details).
Download or read book Wide Field Spectroscopy and the Distant Universe written by Steve J. Maddox and published by World Scientific. This book was released on 1995 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Buildings Energy Conservation written by and published by . This book was released on 1986 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Encyclopedia of Electrochemical Power Sources written by and published by Elsevier. This book was released on 2024-09-16 with total page 5674 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Encyclopedia of Electrochemical Power Sources, Second Edition, is a comprehensive seven-volume set that serves as a vital interdisciplinary reference for those working with batteries, fuel cells, electrolyzers, supercapacitors, and photo-electrochemical cells. With an increased focus on the environmental and economic impacts of electrochemical power sources, this work not only consolidates extensive coverage of the field but also serves as a gateway to the latest literature for professionals and students alike. The field of electrochemical power sources has experienced significant growth and development since the first edition was published in 2009. This is reflected in the exponential growth of the battery market, the improvement of many conventional systems, and the introduction of new systems and technologies. This completely revised second edition captures these advancements, providing updates on all scientific, technical, and economic developments over the past decade. Thematically arranged, this edition delves into crucial areas such as batteries, fuel cells, electrolyzers, supercapacitors, and photo-electrochemical cells. It explores challenges and advancements in electrode and electrolyte materials, structural design, optimization, application of novel materials, and performance analysis. This comprehensive resource, with its focus on the future of electrochemical power sources, is an essential tool for navigating this rapidly evolving field. - Covers the main types of power sources, including their operating principles, systems, materials, and applications - Serves as a primary source of information for electrochemists, materials scientists, energy technologists, and engineers - Incorporates 365 articles, with timely coverage of environmental and sustainability aspects - Arranged thematically to facilitate easy navigation of topics and easy exploration of the field across its key branches - Follows a consistent structure and features elements such as key objective boxes, summaries, figures, references, and cross-references etc., to help students, faculty, and professionals alike
Download or read book Large Scale Scientific Computing written by Ivan Lirkov and published by Springer Nature. This book was released on 2020-02-13 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes revised papers from the 12th International Conference on Large-Scale Scientific Computing, LSSC 2019, held in Sozopol, Bulgaria, in June 2019. The 70 papers presented in this volume were carefully reviewed and selected from 81 submissions. The book also contains two invited talks. The papers were organized in topical sections named as follows: control and optimization of dynamical systems; meshfree and particle methods; fractional diffusion problems: numerical methods, algorithms and applications; pore scale flow and transport simulation; tensors based algorithms and structures in optimization and applications; HPC and big data: algorithms and applications; large-scale models: numerical methods, parallel computations and applications; monte carlo algorithms: innovative applications in conjunctions with other methods; application of metaheuristics to large-scale problems; large scale machine learning: multiscale algorithms and performance guarantees; and contributed papers.
