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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Machine learning mathematical models for incidence estimation during pandemics

Accurate estimates of the incidence of infectious diseases are key for the control of epidemics. However, healthcare systems are often unable to test the population exhaustively, especially when asymptomatic and paucisymptomatic cases are widespread; this leads to significant and systematic under-reporting of the real incidence. Here, we propose a machine learning approach to estimate the incidence of a pandemic in real-time, using reported cases and the overall test rate. In particular, we use Bayesian symbolic regression to automatically learn the closed-form mathematical models that most parsimoniously describe incidence. We develop and validate our models using COVID-19 incidence values for nine different countries, confirming their ability to accurately predict daily incidence. Remarkably, despite the differences in epidemic trajectories and dynamics across countries, we find that a single model for all countries offers a more parsimonious description and is more predictive of actual incidence compared to separate models for each country. Our results show the potential to accurately model incidence in real-time using closed-form mathematical models, providing a valuable tool for public health decision-makers.

Fajardo-Fontiveros, Oscar (ORCID:0000000207058972)↗
DOE OSTI2016

Brady's Geothermal Field - Map of DAS, Nodal, Vibroseis and Reftek Station Deployment

Map of DAS, nodal, vibroseis and Reftek stations during March 2016 deployment. The plot on the left has nodal stations labeled; the plot on the right has vibroseis observations labeled. Stations are shown in map-view using Brady's rotated X-Y coordinates with side plots denoting elevation with respect to the WGS84 ellipsoid. Blue circles denote vibroseis data, x symbols denote DAS (cyan for horizontal and magenta for vertical), black asterisks denote Reftek data, and red plus signs denote nodal data. This map can be found on UW-Madison's askja server at /PoroTomo/DATA/MAPS/Deployment_Stations.pdf

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Utah FORGE: Site Earthquake Animation

This is a .kml earthquake animation covering the period of 1991 - 2011 for the Utah Milford FORGE site. It displays seismic events using different sized bubbles according to magnitude. It covers the general Utah FORGE area (large shaded rectangle) with the final site displayed as a smaller polygon along the northwestern margin. Earthquakes are subdivided into clusters and the time, date, and magnitude of each event is included. Nearby seismic stations are symbolized with triangles. This was created by the University of Utah Seismograph Stations (UUSS).

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Standard atomic weights of the elements 2021 (IUPAC Technical Report)

Following the reviews of atomic-weight determinations and other cognate data in 2015, 2017, 2019 and 2021, the IUPAC (International Union of Pure and Applied Chemistry) Commission on Isotopic Abundances and Atomic Weights (CIAAW) reports changes of standard atomic weights. The symbol A r°(E) was selected for standard atomic weight of an element to distinguish it from the atomic weight of an element E in a specific substance P, designated A r(E, P). The CIAAW has changed the values of the standard atomic weights of five elements based on recent determinations of terrestrial isotopic abundances. The standard atomic weight of argon and lead have changed to an interval to reflect that the natural variation in isotopic composition exceeds the measurement uncertainty of A r(Ar) and A r(Pb) in a specific substance. The standard atomic weights and/or the uncertainties of fourteen elements have been changed based on the Atomic Mass Evaluations 2016 and 2020 accomplished under the auspices of the International Union of Pure and Applied Physics (IUPAP). A r° of Ho, Tb, Tm and Y were changed in 2017 and again updated in 2021.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Henry’s law constants (IUPAC Recommendations 2021)

Henry’s law states that the abundance of a volatile solute dissolved in a liquid is proportional to its abundance in the gas phase. It applies at equilibrium and in the limit of infinite dilution of the solute. For historical reasons, numerous different definitions, names, and symbols are used in the literature to express the proportionality coefficient, denoted the “Henry’s law constant”. Furthermore, a consistent set of recommendations is presented. An important distinction is made between two new recommended reciprocal quantities: “Henry’s law solubility constant” (H s ) and “Henry’s law volatility constant” (H v ). Eight recommended variants of H s and H v are described and relations among them presented.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Marine Corps Base Camp Lejeune Water Quality Dataflow Viewer

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.GIS was used to create point layers from the coordinates representing samples taken along the mainstem and shallow portions of the New River Estuary. The point layers were transformed into linear features and datasets were created for each parameter (salinity, chlorophyll, and turbidity). The line representing each sample collection point was symbolized based on the value of each parameter in the Water Quality Explorer for the dawn samples only. The date and time collected for each sample was used to visualize the sample collection at dawn in the map viewer. Each GIS layer was time enabled with a daily time step interval so that changes in concentrations of salinity, chlorophyll, and turbidity could be observed on a daily basis. In the geodatabase, the layers used for the dawn samples end with “_AM”. The ones without AM at the end include all samples (AM and PM); note that the PM samples are not visualized in the Water Quality Explorer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Native glycosylated HIV-1 Env in silico ensemble

The computationally modeled datasets generated in this study, namely the natively glycosylated SOSIP Env and the uniform mannose-9 glycosylated SOSIP Env ensembles will be submitted as Mendeley dataset server as required by the journal publishers, for public availability. These include two sets of Protein Data Bank (PDB)ensembles of 1000 structures each. The files are in the standardized PDB format. Each of the constituent ensemble structures are separated by the ‘END’ tag within the files. Snapshots from the beginning and end of each data set are given here. The column descriptions are as follows: Col1 –ATOM tag; Col 2 –atom number; COL 3 –atom name; COL4 –residue name; COL 5 –chain identifier; COL 6 –residue number; COL. 7,8,9 –X,Y,Z coordinates of atom in 3Dspace; COL 10 –Occupancy Factor; COL 11 -Temperature factor; COL 12 –segment identifier; COL 13 –element symbol.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Energy Community Atlas

The Energy Community Atlas provides efficient access to authoritative, curated, and relevant data that is vital to supporting energy planning, development, and economic growth across the U.S. In this effort, researchers at the National Energy Technology Laboratory (NETL) are utilizing advanced data visualization and transformation capabilities to develop an integrated, data atlas and resource focused on supporting energy community transitions to new manufacturing opportunities. Specifically, this project is working to find, acquire, integrate, and virtually host in a user-friendly, public and private solution from available resources, relevant to understanding and characterizing fossil energy communities themselves and inform energy planning, development, and economic growth opportunities, including opportunities for co-development to support manufacturing, critical materials, and more. This Atlas when complete is to offer a one-stop-shop for stakeholders to derive new insights to accelerate energy investments and strategic decision support needs. These are following datasets that are available as part of this ongoing project • Energy Community Atlas Map Package - This is ArcPro Map package and it contains all of the symbolized layers along with ArcPro map and geodatabase • Energy Community Atlas ArcGIS REST service - https://www.arcgis.com/apps/mapviewer/index.html?panel=gallery&suggestField=true&layers=537ced69bd88440380a62c2ec8aca30c • README Energy Community Atlas - Read me word document that has details about feature classes in Map package, ArcPro map and ArcGIS Rest Service

Bipartisan Infrastructure Law↗
DOE OSTI2013

VEST: abstract vector calculus simplification in Mathematica

We present a new package, VEST (Vector Einstein Summation Tools), that performs abstract vector calculus computations in Mathematica. Through the use of index notation, VEST is able to reduce scalar and vector expressions of a very general type using a systematic canonicalization procedure. In addition, utilizing properties of the Levi-Civita symbol, the program can derive types of multi-term vector identities that are not recognized by canonicalization, subsequently applying these to simplify large expressions. In a companion paper, we employ VEST in the automation of the calculation of Lagrangians for the single particle guiding center system in plasma physics, a computation which illustrates its ability to handle very large expressions. VEST has been designed to be simple and intuitive to use, both for basic checking of work and more involved computations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Compositional Dataflow Via Abstract Transition Systems

Despite decades of research and development of dataflow analyses within dozens of different compiler infrastructures, analysis of real programs is intractable in practice. The reason is that although a single research group is equipped to model a single well-defined aspect of application behavior, application developers use a very wide range of abstractions and coding techniques within a single application. Since to analyze even a single application all of its complexities must be modeled, researchers must combine analyses from multiple groups into comprehensive analysis frameworks such as OpenAnalysis or LLVM. Analysis composition is expensive in practice, requiring development effort that is quadratic in the number of analyses as well as tight inter-group coordination to maintain consistent APIs to each other’s symbolic abstractions. This paper proposes an approach to building compiler analysis frameworks that simplifies the composition of independently-developed analyses. It formalizes the operation of dataflow analyses in a way that simplifies reasoning about various types of analysis composition. Further, it defines a portable abstraction that can represent the results of many real analyses, making it possible for different analyses to leverage each other’s results with no knowledge of their APIs or internal abstractions and without any coordination between the groups that developed them. We have developed the Fuse compositional analysis framework based on this abstraction, and integrated it in the ROSE [15] compilation system. Our experience is that this approach greatly simplifies composition of program analyses, making it easy to tailor different combinations of program analyses to different input programs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

MOGO: Model-Oriented Global Optimization of Petascale Applications

The MOGO project was initiated under in 2008 under the DOE Program Announcement for Software Development Tools for Improved Ease-of-Use on Petascale systems (LAB 08-19). The MOGO team consisted of Oak Ridge National Lab, Argonne National Lab, and the University of Oregon. The overall goal of MOGO was to attack petascale performance analysis by developing a general framework where empirical performance data could be efficiently and accurately compared with performance expectations at various levels of abstraction. This information could then be used to automatically identify and remediate performance problems. MOGO was be based on performance models derived from application knowledge, performance experiments, and symbolic analysis. MOGO was able to make reasonable impact on existing DOE applications and systems. New tools and techniques were developed, which, in turn, were used on important DOE applications on DOE LCF systems to show significant performance improvements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Water Security Toolkit User Manual Version 1.2.

The Water Security Toolkit (WST) is a suite of open source software tools that can be used by water utilities to create response strategies to reduce the impact of contamination in a water distribution network . WST includes hydraulic and water quality modeling software , optimizati on methodologies , and visualization tools to identify: (1) sensor locations to detect contamination, (2) locations in the network in which the contamination was introduced, (3) hydrants to remove contaminated water from the distribution system, (4) locations in the network to inject decontamination agents to inactivate, remove, or destroy contaminants, (5) locations in the network to take grab sample s to help identify the source of contamination and (6) valves to close in order to isolate contaminate d areas of the network. This user manual describes the different components of WST , along w ith examples and case studies. License Notice The Water Security Toolkit (WST) v.1.2 Copyright c 2012 Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000, there is a non-exclusive license for use of this work by or on behalf of the U.S. government. This software is distributed under the Revised BSD License (see below). In addition, WST leverages a variety of third-party software packages, which have separate licensing policies: Acro Revised BSD License argparse Python Software Foundation License Boost Boost Software License Coopr Revised BSD License Coverage BSD License Distribute Python Software Foundation License / Zope Public License EPANET Public Domain EPANET-ERD Revised BSD License EPANET-MSX GNU Lesser General Public License (LGPL) v.3 gcovr Revised BSD License GRASP AT&T Commercial License for noncommercial use; includes randomsample and sideconstraints executable files LZMA SDK Public Domain nose GNU Lesser General Public License (LGPL) v.2.1 ordereddict MIT License pip MIT License PLY BSD License PyEPANET Revised BSD License Pyro MIT License PyUtilib Revised BSD License PyYAML MIT License runpy2 Python Software Foundation License setuptools Python Software Foundation License / Zope Public License six MIT License TinyXML zlib License unittest2 BSD License Utilib Revised BSD License virtualenv MIT License Vol Common Public License vpykit Revised BSD License Additionally, some precompiled WST binary distributions might bundle other third-party executables files: Coliny Revised BSD License (part of Acro project) Dakota GNU Lesser General Public License (LGPL) v.2.1 PICO Revised BSD License (part of Acro project) i Revised BSD License Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of Sandia National Laboratories nor Sandia Corporation nor the names of its con- tributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IM- PLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUD- ING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. ii Acknowledgements This work was supported by the U.S. Environmental Protection Agency through its Office of Research and Development (Interagency Agreement # DW8992192801). The material in this document has been subject to technical and policy review by the U.S. EPA, and approved for publication. The views expressed by individual authors, however, are their own, and do not necessarily reflect those of the U.S. Environmental Protection Agency. Mention of trade names, products, or services does not convey official U.S. EPA approval, endorsement, or recommendation. The Water Security Toolkit is an extension of the Threat Ensemble Vulnerability Assessment-Sensor Place- ment Optimization Tool (TEVA-SPOT), which was also developed with funding from the U.S. Environ- mental Protection Agency through its Office of Research and Development (Interagency Agreement # DW8992192801). The authors acknowledge the following individuals for their contributions to the devel- opment of TEVA-SPOT: Jonathan Berry (Sandia National Laboratories), Erik Boman (Sandia National Laboratories), Lee Ann Riesen (Sandia National Laboratories), James Uber (University of Cincinnati), and Jean-Paul Watson (Sandia National Laboratories). iii Acronyms ATUS American Time-Use Survey BLAS Basic linear algebra sub-routines CFU Colony-forming unit CVAR Conditional value at risk CWS Contamination warning system EA Evolutionary algorithm EDS Event detection system EPA U.S. Environmental Protection Agency EC Extent of Contamination ERD EPANET results database file GLPK GNU Linear Programming Kit GRASP Greedy randomized adaptive sampling process HEX Hexadecimal HTML HyperText markup language INP EPANET input file LP Linear program MC Mass consumed MILP Mixed integer linear program MIP Mixed integer program MSX Multi-species extension for EPANET NFD Number of failed detections NS Number of sensors NZD Non-zero demand PD Population dosed PE Population exposed PK Population killed TAI Threat assessment input file TCE Tailed-conditioned expectation TD Time to detection TEC Timed extent of contamination TEVA Threat ensemble vulnerability assessment TSB Tryptic soy broth TSG Threat scenario generation file TSI Threat simulation input file VAR Value at risk VC Volume consumed WST Water Security Toolkit YML YAML configuration file format for WST iv Symbols Notation Definition Example { , } set brackets { 1,2,3 } means a set containing the values 1,2, and 3. [?] is an element of s [?] S means that s is an element of the set S . [?] for all s = 1 [?] s [?] S means that the statement s = 1 is true for all s in set S . P summation P n i =1 s i means s 1 + s 2 + * * * + s n . \ set minus S \ T means the set that contains all those elements of S that are not in set T . %7C given %7C is used to define conditional probability. P ( s %7C t ) means the prob- ability of s occurring given that t occurs. %7C ... %7C cardinality Cardinality of a set is the number of elements of the set. If set S = { 2,4,6 } , then %7C S %7C = 3. v

Klise, Katherine A.↗
DOE OSTI2016

Limiting Magnitude, τ, t eff , and Image Quality in DES Year 1

The Dark Energy Survey (DES) is an astronomical imaging survey being completed with the DECam imager on the Blanco telescope at CTIO. After each night of observing, the DES data management (DM) group performs an initial processing of that night's data, and uses the results to determine which exposures are of acceptable quality, and which need to be repeated. The primary measure by which we declare an image of acceptable quality is $\tau$, a scaling of the exposure time. This is the scale factor that needs to be applied to the open shutter time to reach the same photometric signal to noise ratio for faint point sources under a set of canonical good conditions. These conditions are defined to be seeing resulting in a PSF full width at half maximum (FWHM) of 0.9" and a pre-defined sky brightness which approximates the zenith sky brightness under fully dark conditions. Point source limiting magnitude and signal to noise should therefore vary with t in the same way they vary with exposure time. Measurements of point sources and $\tau$ in the first year of DES data confirm that they do. In the context of DES, the symbol $t_{eff}$ and the expression "effective exposure time" usually refer to the scaling factor, $\tau$, rather than the actual effective exposure time; the "effective exposure time" in this case refers to the effective duration of one second, rather than the effective duration of an exposure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Explosive Formulation Code Naming SOP

The purpose of this SOP is to provide a procedure for giving individual HME formulations code names. A code name for an individual HME formulation consists of an explosive family code, given by the classified guide, followed by a dash, -, and a number. If the formulation requires preparation such as packing or aging, these add additional groups of symbols to the X-ray specimen name.

42 ENGINEERING↗
DOE OSTI2016

360⁰ -View of Quantum Theory and Ab Initio Simulation at Extreme Conditions: 2014 Sanibel Symposium

The Sanibel Symposium 2014 was held February 16-21, 2014, at the King and Prince, St. Simons Island, GA. It was successful in bringing condensed-matter physicists and quantum chemists together productively to drive the emergence of those specialties. The Symposium had a significant role in preparing a whole generation of quantum theorists. The 54th Sanibel meeting looked to the future in two ways. We had 360⁰-View sessions to honor the exceptional contributions of Rodney Bartlett (70), Bill Butler (70), Yngve Öhrn (80), Fritz Schaefer (70), and Malcolm Stocks (70). The work of these five has greatly impacted several generations of quantum chemists and condensed matter physicists. The “360⁰” is the sum of their ages. More significantly, it symbolizes a panoramic view of critical developments and accomplishments in theoretical and computational chemistry and physics oriented toward the future. Thus, two of the eight 360⁰-View sessions focused specifically on younger scientists. The 360⁰-View program was the major component of the 2014 Sanibel meeting. Another four sessions included a sub-symposium on ab initio Simulations at Extreme Conditions, with focus on getting past the barriers of present-day Born-Oppenheimer molecular dynamics by advances in finite-temperature density functional theory, orbital-free DFT, and new all-numerical approaches.

360-view↗
DOE OSTI2016

Development and Evaluation of Algorithms to Improve Small- and Medium-Size Commercial Building Operations

Small- and medium-sized (<100,000 sf) commercial buildings (SMBs) represent over 95% of the U.S. commercial building stock and consume over 60% of total site energy consumption. Many of these buildings use rudimentary controls that are mostly manual, with limited scheduling capability, no monitoring or failure management. Therefore, many of these buildings are operated inefficiently and consume excess energy. SMBs typically utilize packaged rooftop units (RTUs) that are controlled by an individual thermostat. There is increased urgency to improve the operating efficiency of existing commercial building stock in the U.S. for many reasons, chief among them is to mitigate the climate change impacts. Studies have shown that managing set points and schedules of the RTUs will result in up to 20% energy and cost savings. Another problem associated with RTUs is short-cycling, where an RTU goes through ON and OFF cycles too frequently. Excessive cycling can lead to excessive wear and lead to premature failure of the compressor or its components. The short cycling can result in a significantly decreased average efficiency (up to 10%), even if there are no physical failures in the equipment. Also, SMBs use a time-of-day scheduling is to start the RTUs before the building will be occupied and shut it off when unoccupied. Ensuring correct use of the zone set points and eliminating frequent cycling of RTUs thereby leading to persistent building operations can significantly increase the operational efficiency of the SMBs. A growing trend is to use low-cost control infrastructure that can enable scalable and cost-effective intelligent building operations. The work reported in this report describes three algorithms for detecting the zone set point temperature, RTU cycling rate and occupancy schedule detection that can be deployed on the low-cost infrastructure. These algorithms only require the zone temperature data for detection. The algorithms have been tested and validated using field data from a number of RTUs from six buildings in different climate locations. Overall, the algorithms were successful in detecting the set points and ON/OFF cycles accurately using the peak detection technique and occupancy schedule using symbolic aggregate approximation technique. The report describes the three algorithms, results from testing the algorithms using field data, how the algorithms can be used to improve SMBs efficiency, and presents related conclusions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

A Study of China s Explosive Growth in the Plug-in Electric Vehicle Market

The year 2015 marks a turning point in China s plug-in electric vehicle (PEV) or new energy vehicle (NEV) industry, with an explosive growth in both productions and sales, following the gloomy period of 2009-2012. The PEV production in 2015 reached a record level of nearly 380,000 units, a 352 % increase from 2014, making China the largest PEV market in the world. For the potential implications on energy and the environment, it is worth studying the driving forces of China s PEV market and understanding its future trajectory and dynamics. The key findings of this report are listed in the following. Though controversial, the government monetary incentives have played a significant role to impel China to be the largest light PEV (191,100 units) market in the world. Chinese vehicle buyers appear more price sensitive on PEVs. Inexpensive low-cost micro electric vehicles are the most popular vehicle model in China s PEV market (38.9 % of the PEV market in 2015). In contrast, the premium or luxury vehicles are more popular in the gasoline vehicle segment. In fact, China is expected to be the largest premium car market in 2016. The PEV sales growth is primarily possible because of the young domestic private-owned auto manufacturers, which are mostly located in south China. Top-tier conventional vehicle automakers in China appear to be less proactive in the PEV market, based on market shares. This is in clear contrast to the U.S. market, where major automakers are generally the primary players in the PEV market. The PEVs produced by the domestic automakers are concentrated in the low-end market segment, while the high-end vehicle segment is dominated by the foreign brands. At present, the substantial market growth and government subsidies afford the domestic entrants to quickly gain profits in the low-end segment. The PEV consumers in China are very sensitive to the vehicle price, thus prefer the PEVs with cheaper prices after government subsidies, and care less about the driving quality and comfort. In contrast, most PEV consumers in the United States (U.S.) have higher incomes, view the PEVs as a high-status symbol, and care less about the vehicle prices, and therefore welcome the premium PEVs more in the U.S. The PEV financial subsidies by the Chinese government are divided into three stages based on the strategic directions and policies. In 2009 2012, government incentives concentrated on the public fleet vehicles, while excluding the individual consumers from the subsidies in most cities. In 2013 2015, comprehensive central/local government incentives were extended to all vehicle purchasers including the individual buyers in most cities, which was conducive to the phenomenal growth of the PEV sales. For years 2016 to 2020, monetary incentives are being phased out and will be substituted by other non-monetary incentives (such as the standards for Chinese Cooperate Average Fuel Consumption and New Energy Vehicle Credits) for the sustainable development of the PEV market. The PEV subsidy fraud has drawn attention by the central government, which prompts the government to be more prudent about monetary incentives. With the advantage of high acceptance in the PEV market and integrated EV charging infrastructure, the region with better economic development brings a more aggressive PEV roll-out plan to the municipalities who are more willing to solve the local urban pollution while keeping the automotive market in sustainable growth. On the one hand, the local automakers are offered abundant subsidies from the Chinese government to those who intend to help the Chinese automotive industry seize the industrial upgrading opportunity to transform its manufacturing sector, and they have taken most shares of the PEV market. On the other hand, facing the trade barriers, the foreign automakers have dominated the premium PEV sales in China, although their total market shares in the PEV market are much less than the domestic automakers. In diverse selectable alternative fuel vehicle technologies, China has put its focus on the PEV technologies for the technological modernization in the automotive industry; the research and development in fuel cell vehicle technologies in China is less competitive compared with other countries such as Japan and the U.S. With the demand of batteries from the PEV automakers, the Chinese EV battery industry is aggressively expanding. It has risks in excessive production capacity, and faces the challenges from the competitors from Japan and South Korea.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

The Threat Among Us: Insiders Intensify Aviation Terrorism

Aviation terrorism is powerful and symbolic, and will likely remain a staple target for terrorists aiming to inflict chaos and cause mass casualties similar to the 9/11 attacks on the U.S. The majority of international and domestic aviation terrorist attacks involves outsiders, or people who do not have direct access to or affiliation with a target through employment. However, several significant attacks and plots against the industry involved malicious employees motivated by suicide or devotion to a terrorist organization. Malicious insiders’ access and knowledge of aviation security, systems, networks, and infrastructure is valuable to terrorists, providing a different pathway for attacking the industry through the insider threat. Indicators and warnings of insider threats in these cases exist, providing insight into how security agencies, such as the Transportation Security Administration, can better predict and identify insider involvement. Understanding previous aviation insider threat events will likely aid in stimulating proactive security measures, rather than reactive responses. However, similar to traditional airport security measures, there are social, political, and economic challenges in protecting against the insider threat, including privacy concerns and cost-benefit analysis.

99 GENERAL AND MISCELLANEOUS↗