COMPUTATIONAL MODELING AND SIMULATION TECHNIQUES FOR MANAGING RAIL–URBAN INTERFACE CONSTRAINTS IN METROPOLITAN TRANSPORTATION SYSTEMS

This paper provides an overview of the tools used to conduct independent modeling and simulation of Artemis 1 separation events and highlights challenges and lessons learned across a decade of analysis. An overview of each of the tools along with the process flow and key components of maintaining independence from the Program’s baseline tool set will be provided. In addition, each of the separation analyses conducted will be discussed, making note of key models incorporated for each event and unique challenges that were addressed. The technical work described in this paper is part of an on-going technical assessment conducted by the NASA Engineering and Safety Center to develop and maintain an independent modeling and simulation capability in support of Space Launch System (SLS) and Multi-Purpose Crew Vehicle (MPCV) throughout design, verification, and flight readiness cycles. For Artemis 1, an end-to-end analysis approach was taken with events simulated from launch to re-entry. This paper will focus on the separation events, including liftoff clearance analysis, solid rocket booster (SRB) separation from Core Stage (CS), Service Module (SM) panel jettison, ICPS / Core Stage Separation, and MPCV/ ICPS separation. To assess separation clearances, the NESC has developed a high fidelity, independent 6-degree of freedom (DOF) simulation of the separation events. The simulation was developed using the Program to Optimize Simulated Trajectories II (POST2). POST2 is an industry standard flight trajectory optimization and simulation tool that is Class D compliant and follows NASA NPR 7150.2, which includes regression testing, unit testing, and configuration control of the simulation. The primary objective of the SLS separation and clearance analyses was to estimate the clearances between different vehicle components and/or ground support equipment (GSE) during separation events. The clearance is defined as the minimum distance from any point on one 3D geometry model associated with one vehicle component (or GSE) to any point on another 3D geometry model associated with a vehicle component separating from the main body. The vehicle geometry models used by the NESC to compute the separation clearances were derived from CAD models. POST2 simulation results were post processed in the Exploration Visualization Environment (EVE) tool to compute clearances, and detect recontact occurrences, if any, between the separating stages. EVE is a simulation, visualization, and analysis system designed to integrate time-based dynamics data with detailed graphical models in a full-scale virtual environment. EVE was used to simultaneously calculate more than 30 different separation clearances by “driving” detailed vehicle geometry models with position and attitude time history data obtained from the POST2 simulation. EVE displays each clearance distance visually, at any given instant of time, with a straight line connecting the two closest points on each object and records the time history of the clearance distance in a file. If the clearance reduces to zero, then EVE reports it as a recontact. To perform separation analyses, POST2 Monte Carlo analyses were performed by running 2000 dispersed cases that included over hundreds of uncertainties and dispersions for a range of simulation models including aerodynamics, propulsion, navigation sensors, control actuators, slosh and flexible body dynamics, and winds and atmosphere. Clearances were computed for each of the dispersed Monte Carlo trajectories and overall separation performance was statistically assessed. Over the past decade the POST2 simulation and EVE visualization tools have been used to perform detailed assessments of the separation events that occur during the Artemis 1 ascent. To support these assessments, numerous unique simulation models were developed and integrated into the standard suite of POST2 simulation models to address and resolve key concerns specific to each of the Artemis 1 separation events. In addition to presenting an overview of the multi-body 6-DOF simulation and separation analysis capability, the paper will discuss the integration of key simulation models such as flexible body dynamics, slosh dynamics, separation mechanisms, multi-body aerodynamics, and environmental models. Additional details are provided about other challenges that were addressed, including the use of a convex hull to reduce computational time for clearance calculations, the modeling of incidental recontact during separation events, and the capability to simulate failure scenarios.

To provide insights for artisanal recreational fisheries management, using Belize as a case study, our research addressed the following research question: What is the natural resource base in terms of the fish species, typology of users, and general management regulations comprising artisanal recreational fisheries in Belize? To answer it, a mixed method approach, which included social and biological surveys, was used. Our results indicated: (1) there is a mismatch in the very definition of “recreational fisheries” between the fishery managers and resource users; (2) current management regulates the so called “sport fishing,” whereas three other recorded fisheries—reef fishing, blue fishing, and local recreational fishing—remain unregulated; (3) 26 bony fish species in the study area; and (4) the direct users (fishers) are primarily non-residents, whereas the indirect users (service providers) are residents. Our study suggests that any management plan for these fisheries should consider local complexities and stakeholders’ inputs.

The aging of the nuclear weapons stockpile in the US, due to the end of the Cold War and a halt in design and production of new nuclear weapons, has brought demanding technical challenges to the US Department of Energy's nuclear weapons laboratories: Los Alamos, Lawrence Livermore, and Sandia National Laboratories. As stewards of the nation's nuclear deterrent, our mission is to maintain a safe, secure, and reliable nuclear weapons stockpile without further underground nuclear testing. This mission is an enormous undertaking, and the Accelerated Strategic Computing Initiative (ASCI) program has a critical role in meeting these challenges within the Science Based Stockpile Stewardship program. One of the ASCI program's major goals is to create the leading-edge computational modeling and simulation capabilities necessary to shift the nation from nuclear test based methods to simulation based methods. Enabling this shift is a major challenge, not only in that it changes the way we certify the performance, safety, security, and reliability of nuclear weapons, but also because we must establish high performance modeling and simulation as an essential technology for stockpile certification. This new certification paradigm means embracing a simulation based design and engineering approach, rather than using traditional design and test methods.

In the last two decades, numerical models have become well-recognized and widely adopted tools to investigate stenting procedures. Due to limited computational resources and modeling capabilities, early numerical studies only involved simplified cases and idealized stented arteries. Nowadays, increased computational power allows for numerical models to meet clinical needs and include more complex cases such as the implantation of multiple stents in bifurcations or curved vessels. Interesting progresses have been made in the numerical modeling of stenting procedures both from a structural and a fluid dynamics points of view. Moreover, in the drug eluting stents era, new insights on drug elution capabilities are becoming essential in the stent development. Lastly, image-based methods able to reconstruct realistic geometries from medical images have been proposed in the recent literature aiming to better describe the peculiar anatomical features of coronary vessels and increase the accuracy of the numerical models. In this light, this review provides a comprehensive analysis of the current state-of-the-art in this research area, discussing the main methodological advances and remarkable results drawn from a number of significant studies.

Modeling and simulation challenges pursued by the Consortium for Advanced Simulation of Light Water Reactors (CASL)

When dangerous chemical or biological releases occur in the atmosphere, emergency responders and decision makers must assess exposure rates to the affected population, establish evacuation routes, and allocate medical resources We have been working to improve the scientific basis for making such decisions. We believe that future rapid response teams, from LLNI, and other centers of expertise, will use a variety of atmospheric sensors and atmospheric computer models to predict and characterize the movement of chemical or biological releases in urban environments, and that LLNL is likely to contribute expertise in this area. A key advance will be to merge the information and capabilities of computer models with real-time atmospheric data from sensors. The resulting product will dynamically interpolate and extrapolate the raw sensor data into a coordinated ''picture'' or interpretation of the developing flow scenario. The scientific focus of the project was the exploration and development of algorithms to fuse lidar data (which measure wind speed much as a police radar measures vehicle speed) and a dispersion model into a single system. Our goal was to provide the scientific foundation for a combined lidar/model approach capable of accurately tracking the evolution of atmospheric releases on distance scales of about 20 km. The fundamental idea is to create feedbacks, so that lidar data can be used for wind field inputs into a dispersion model, which would, in turn, guide lidar data acquisition by directing more intensive scanning to regions where more data are key to improving the modeling. We created a database of synthetic lidar data that can be used to test algorithms relating to a combined lidar/dispersion model. We obtained the data, which represent nocturnal atmospheric drainage flows in the Salt Lake City Basin, from calculations on the LLNL ASCI White supercomputer with a computational fluid dynamics model running in large-eddy simulation mode. A simple modification of the resulting air-flow data produced radial velocity wind field data, which may be directly compared with real lidar data and substituted for them. We have produced a short animation (which can be viewed in the CD-ROM version of this article) representing drainage flow from the mountains. The assumed position of the lidar was that of an actual lidar that took data in the Urban Dispersion Project, funded by DOE, in the fall of 2000. We studied the ''Terminal Winds'' project at the Lincoln Laboratory of the Massachusetts Institute of Technology. We analyzed algorithms and approaches used by other scientists on related or relevant projects. We evaluated the Gauss-Markov theorem approach and concluded that it will be useful in designing an advanced sensor integration system for incorporating lidar into numerical models, and, in particular, to build a single interpretation of a flow field based on potentially conflicting sensor data We began development of a script-based ''test'' laboratory, which samples the database and provides input to a dispersion model, which was ported and tested on the Frost computer system at LLNL. Our results demonstrate that specially sampled data from numerical models can indeed be a useful surrogate for actual lidar data which can only be gathered currently at great expense. The further development of the algorithms and ideas relating to this project continue at Arizona State University (ASU) where the PI is now an Assistant Professor of Mechanical and Aerospace Engineering. LLNL and ASU have recently established a collaboration entitled ''Advanced Sensor Integration into NARAC's Atmospheric Data Assimilation Program'' which we believe will benefit from the groundwork provided by this LDRD.

In this research, we designed a universal graph model. We targeted this work on improving graph data organization representation, flexible formation of graph substructures for complex system modeling and generic processing of data organization. We form coherently composed graph modeling features including inheritance hierarchy of basic graph types, data participating graphs of multiple aspects, hierarchically composed and connected graphs, and property-based graph models based on existing graph models. Design cases are used to illustrate its achievement of our design goal. Keywords—graph theory; graph model, multi-aspect graph; hierarchical graph I. INTRODUCTION Computer modeling plays a key role to apply computer's capability in various fields of applications. Effective support of computer modeling should consist of data representation capability, data access and navigation capability, and generic operations for forming more general and reusable generic algorithms. As computer applications keep growing complex in wider areas, we need enhanced computer models capable of supporting these applications. Graph data models are one of the most extensively used discrete mathematical models in computer modeling of various applications from VLSI circuit design, computer system design and modeling, network modeling, etc. Traditional graph libraries such as LEDA(1), Boost Graph Library(2), LINK(3), and GraphStream(4) focuses on single- level directed and undirected graph modeling. Lee's work(5) utilized decorator and visitor patterns to add new vertex data and attach processing during graph traversal. Pizzonia's (6) employed static object-oriented extension of graph property classes associated with corresponding graph operations. Bertault(7) employed an extensible graph property class hierarchy and dynamic property checking. Directed and undirected hypergraphs are not supported in these approaches. Hyperedges in hypergraphs can be represented as vertices in ordinary graphs. Hypergraphs cannot be treated as super types of directed and undirected graphs to support generic algorithms with ordinary graphs. On data organization point of view, these approaches provide various graph organization types but only as single- level specialized graph type. Each of them should be utilized distinctly. Once these graph models need to be combined in a complex data model, designers should add artificial data structures to join them together. Still, such combined data model or its selected subparts cannot be viewed and utilized as if in a single graph model. This requires designers to add more application-specific gluing data structures, processing codes of distinct graph substructures and their gluing logic, and semantically similar but redundant non-generic codes. It thus hinders effective development and reuse of computer models for various complex applications. From our literature survey, we did not find any previous work providing combinational features for flexibly composing graph structures. Our design goal lies in three improvement directions, representation of complex system data organization, flexible formation of graph substructures for processing, and generic processing of data organization as well as individual data. Our main approach is to form coherently composed graph modeling features including inheritance hierarchy of basic graph types, vertex data participating in graphs of multiple aspects, hierarchically composed and connected graphs, and property-based graph models based on existing graph models. It forms a universal graph model of combinations of complex graph-oriented data organizations, flexibly forms various virtual graph substructures for complex system modeling and processing, and support generic processing capability at the graph structure levels and at the leaf data levels. In section 2, we describe refined design goals and the approach of our work. In the following sections, we in sequence introduce planned composed graph modeling features of our universal graph model, including generic accesses among basic graph models, joining multiple graphs into a multi-aspect graph model, generic structuring of graph models, and generic accesses of property-based graph models. In section 7, we introduce its software design and a design case. The last section concludes this research.

The structure of Petri net model is relative fixed after it is built, so it cant describe dynamic change behavior of real system structure easily. Description formalness, coupling mechanism and simulation method were presented, the dynamic change of Petri net structure in simulation run was realized based on the idea of software component design. The reuse capability of Petri net model is enhanced, integration with other models is convenience and hierarchical modeling mode is realized, and the capability of modeling and simulation of Petri net is improved.

As they are maturing—i.e., as they are becoming validated, calibrated and refined—computational emulation models of organizations are evolving into: powerful new kinds of organizational design tools for predicting and mitigating organizational riskss and flexible new kinds of organizational theorem-provers for validating extant organization theory and developing new theory. Over the past 50 years, computational modeling and simulation have had enormous impacts on the rate of advancement of knowledge in fields like physics, chemistry and, more recently, biologys and their subsequent application has enabled whole new areas of engineering practice. In the same way, as our young discipline comes of age, computational organizational models are beginning to impact behavioral, organizational and economic science, and management consulting practice. This paper attempts to draw parallels between computational modeling in natural sciences and computational modeling of organizations as a contributor to both social science and management practice. To illustrate the lifecycle of a computational organizational model that is now relatively mature, this paper traces the evolution of the Virtual Design Team (VDT) computational modeling and simulation research project at Stanford University from its origins in 1988 to the present. It lays out the steps in the process of validating VDT as a “computational emulation” model of organizations to the point that VDT began to influence management practice and, subsequently, to advance organizational science. We discuss alternate research trajectories that can be taken by computational and mathematical modelers who prefer the typical natural science validation trajectory—i.e., who attempt to impact organizational science first and, perhaps subsequently, to impact management practice. The paper concludes with a discussion of the current state-of-the-art of computational modeling of organizations and some thoughts about where, and how rapidly, the field is headed.

The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the surety and reliability of the U.S. nuclear stockpile. The SSP uses past nuclear test data along with current and future non-nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of current facilities and programs along with new experimental facilities and computational enhancements to support these programs. The Advanced Simulation and Computing Program (ASC)1 is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification, to study advanced nuclear-weapons design and manufacturing processes, to analyze accident scenarios and weapons aging, and to provide the tools to enable Stockpile Life Extension Programs (SLEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balanced resource, including technical staff, hardware, simulation software, and computer science solutions. In its first decade, the ASC strategy focused on demonstrating simulation capabilities of unprecedented scale in three spatial dimensions. In its second decade, ASC is focused on increasing its predictive capabilities in a three-dimensional simulation environment while maintaining the support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (focused on sufficient resolution, dimensionality and scientific details); to quantify critical margins and uncertainties (QMU); and to resolve increasingly difficult analyses needed for the SSP. Moreover, ASC has restructured its business model from one that was very successful in delivering an initial capability to one that is integrated and focused on requirements-driven products that address long-standing technical questions related to enhanced predictive capability in the simulation tools. ASC must continue to meet three objectives: Objective 1. Robust Tools--Develop robust models, codes, and computational techniques to support stockpile needs such as refurbishments, SFIs, LEPs, annual assessments, and evolving future requirements. Objective 2--Prediction through Simulation. Deliver validated physics and engineering tools to enable simulations of nuclear-weapons performances in a variety of operational environments and physical regimes and to enable risk-informed decisions about the performance, safety, and reliability of the stockpile. Objective 3. Balanced Operational Infrastructure--Implement a balanced computing platform acquisition strategy and operational infrastructure to meet Directed Stockpile Work (DSW) and SSP needs for capacity and high-end simulation capabilities.

Sandia National Laboratories has a long history of significant contributions to the high performance community and industry. Our innovative computer architectures allowed the United States to become the first to break the teraFLOP barrier—propelling us to the international spotlight. Our advanced simulation and modeling capabilities have been integral in high consequence US operations such as Operation Burnt Frost. Strong partnerships with industry leaders, such as Cray, Inc. and Goodyear, have enabled them to leverage our high performance computing (HPC) capabilities to gain a tremendous competitive edge in the marketplace. As part of our continuing commitment to providing modern computing infrastructure and systems in support of Sandia missions, we made a major investment in expanding Building 725 to serve as the new home of HPC systems at Sandia. Work is expected to be completed in 2018 and will result in a modern facility of approximately 15,000 square feet of computer center space. The facility will be ready to house the newest National Nuclear Security Administration/Advanced Simulation and Computing (NNSA/ASC) Prototype platform being acquired by Sandia, with delivery in late 2019 or early 2020. This new system will enable continuing advances by Sandia science and engineering staff in the areas of operating system R&D, operation cost effectiveness (power and innovative cooling technologies), user environment and application code performance.

A vital part of the licensing process for advanced (non-LWR) nuclear reactor developers in the United States is the assessment of the reactor’s source term, i.e., the potential release of radionuclides from the reactor system to the environment during normal operations and accident sequences. In comparison to source term assessments which follow a bounding approach with conservative assumptions, a mechanistic approach to modeling radionuclide transport, which realistically accounts for transport and retention phenomena, is expected to be used for advanced reactor systems. As the designs of advanced reactors increase in maturity and progress towards licensing, there is a need to advance modeling and simulation capabilities in analyzing the mechanistic source term (MST) of a prospective reactor concept. In the present work, a survey is provided of existing computational capabilities for the modeling of advanced reactors MSTs. The following reactors are considered: high temperature gas reactors (HTGR); molten salt reactors (MSR) which include salt-fueled reactors and fluoride salt-cooled high temperature reactors (FHR); and sodium- and lead-cooled fast reactors (SFR, LFR). A review of relevant codes which may be useful in providing information to MST analyses is also completed, including codes that have been used for source term analyses of LWRs, as well as those being developed for other aspects of advanced reactor system modeling such as reactor physics, thermal hydraulics, and chemistry. A discussion of MST modeling capabilities for each reactor type is provided with additional focus on important phenomena and functional requirements. Additionally, a comprehensive survey is provided of tools for consequence modeling such as atmospheric transport and dispersion (ATD).

Microreactors are small mobile transportable nuclear reactors with thermal power less than 20 MWt that are designed to meet the needs of remote areas, military installations, emergency operations, and disaster relief zones. These reactor are concepts that are intended to be factory-manufacturable, easily transportable, and will allow for semi- or full-autonomous operation. To assist with development of microreactors, modeling and experimentation need to be performed with verification and validation to gain confidence in the models and tools. The objective of this study is apply advanced modeling and simulation capabilities being developed by the DOE Office of Nuclear Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to perform integrated modeling and simulation capability for multiphysics simulation of the microreactor concepts. This activity will provide an opportunity to exercise the codes to provide both gain experience and to provide feedback to the developers.

Understanding the constraints and limitations of various potential hull structure materials and armor is paramount in design considerations of future combat vehicles. Developing and applying theoretical and computational models that guide the development of design criteria and fabrication processes of high ballistic-resistant material are essential. The ultimate objective is to develop and field a contingency armor that is thin and lightweight, but with a very high level of overpressure protection system that provides low penetration depths. Therefore, performing multiscale computational modeling and simulation of the ballistic response of fighting vehicles made of high performance materials under hypervelocity projectile impact is invaluable. However, as soon as material failure dominates a deformation process, the material increasingly displays strain softening (localization) and the finite element computations are considerably affected by the mesh size and alignment and gives non-physical descriptions of the damaged regions and failure of solids. Therefore, the effective use of existing Finite Element Codes in the direct simulation of hypervelocity impacts by projectiles is limited by the dependence of the size of localized failure regions on the mesh size and alignment. As a remedy to this situation, a micromechanical constitutive model that couples the anisotropic thermo-viscodamage mechanism with the thermohypoelasto-viscoplastic deformation is formulated in [1–3] based on the non-local laws of the thermodynamics. Explicit and implicit microstructural length scale measures, which preserve the well-posed nature of the differential equations, are introduced through the use of the viscosity and gradient localization limiters. The enhanced nonlocal gradient-dependent theory formulates a constitutive framework on the continuum level that is used to bridge the gap between the micromechanical theories and the classical (local) continuum theories. They are successful in explaining the size effects encountered at the micron scale and in preserving the well-posedeness of the initial boundary value problem governing the solution of material instability triggering strain localization. Moreover, viscosity (rate dependency) allows the spatial difference operator in the governing equations to retain its hyperbolicity and the initial boundary value problem is well-posed. Model capabilities are preliminarily illustrated for the dynamic localization of inelastic flow in adiabatic shear bands and the perforation of Weldox 460E steel plates with by a deformable blunt projectile at various high impact speeds. Comparisons with the experimental results in [4] are performed. The micro-damage model used to predict material behavior under dynamic loading conditions was earlier presented in [1–3]. Thus, only the main equations will be given in the following. The model is based on the nonlocal gradient-dependent theory. It includes the von Mises yield criterion, the non-associated flow rules, isotropic and anisotropic strain hardening, strain rate hardening, softening due to adiabatic heating and anisotropic damage evolution, and finally a

The Fast Ignition (FI) Concept for Inertial Confinement Fusion has the potential to provide a significant advance in the technical attractiveness of Inertial Fusion Energy (IFE) reactors. FI differs from conventional “central hot spot” (CHS) target ignition by decoupling compression from heating: using the laser (or heavy ion beam or Z pinch) drive pulse (10’s of ns) to create a dense fuel and a second, much shorter (~10 ps) high intensity pulse to ignite a small region of it. There are two major physics issues concerning this concept; controlling the laser-induced generation of large electron currents and their propagation through high density plasmas. This project has addressed these two significant scientific issues in Relativistic High Energy Density (RHED) physics. Learning to control relativistic laser matter interaction (and the limits and potential thereof) will enable a wide range of applications. While these physics issues are of specific interest to inertial fusion energy science, they are also important for a wide range of other HED phenomena, including high energy ion beam generation, isochoric heating of materials, and the development of high brightness x-ray sources. Generating, controlling, and understanding the extreme conditions needed to advance this science has proved to be challenging: Our studies have pushed the boundaries of physics understanding and are at the very limits of experimental, diagnostic, and simulation capabilities in high energy density laboratory physics (HEDLP). Our research strategy has been based on pursuing the fundamental physics underlying the Fast Ignition (FI) concept. We have performed comprehensive study of electron generation and transport in fast-ignition targets with experiments, theory, and numerical modeling. A major issue is that the electrons produced in these experiments cannot be measured directly—only effects due to their transport. We focused mainly on x-ray continuum photons from bremsstrahlung and x-ray line radiation from K-shell fluorescence. Integrated experiments, which combine target compression with short-pulse laser heating, yield additional information on target heating efficiency. This indirect way of studying the underlying behavior of the electrons must be validated with computational modeling to understand the physics and improve the design. This program execution required a large, well-organized team and it was managed by a joint Collaboration between General Atomics (GA), Lawrence Livermore National Laboratory (LLNL), and the Laboratory for Laser Energetics (LLE). The Collaboration was formed 8 years ago to understand the physics issues of the Fast Ignition concept, building on the strengths of each partner. GA fulfills its responsibilities jointly with the University of California, San Diego (UCSD), The Ohio State University (OSU) and the University of Nevada at Reno (UNR). Since RHED physics is pursued vigorously in many countries, international researchers have been an important part of our efforts to make progress. The division of responsibility was as follows: (1) LLE had primary leadership for channeling studies and the integrated energy transfer, (2) LLNL led the development of measurement methods, analysis, and deployment of diagnostics, and (3) GA together with UCSD, OSU and UNR studied the detailed energy-transfer physics. The experimental program was carried out using the Titan laser at the Jupiter Laser Facility at LLNL, the OMEGA and OMEGA EP lasers at LLE and the Texas Petawatt laser (TPW) at UT Austin. Modeling has been pursued on large computing facilities at LLNL, OSU, and UCSD using codes developed (by us and others) within the HEDLP program, commercial codes, and by leveraging existing supercomputer codes developed by the NNSA ICF program. This Consortium brought together all the components—resources, facilities, and personnel—necessary to accomplish its aggressive goals. The ACE Program has been strongly collaborative, taking advantage of the expertise of the participating institutions to provide a research effort that is far greater than the sum of its parts. The results of this work have firmly strengthened the scientific foundation from which the viability of FI and other applications can be evaluated. Program execution has also led to improved diagnostics for probing dense, hot plasmas, detailed understanding of high-current, relativistic electron energy generation and transport across boundaries and into dense plasmas, and greatly enhanced predictive modeling capabilities. One important aspect of this program was the involvement and training of young scientists including postdoctoral fellows and graduate students. During the entire 8 years of FI and ACE project period since 2005, more than fifteen graduate students completed their doctoral dissertations including three from OSU and two from UCSD in last three years. This project generated an impressive forty articles in high quality journals including nine (including two under review) in Physical Review Letters during the last funding period since 2011.