Search NASA⌕ Search

SEARCH · Search NASA

Results for “programming model”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A coupled hydrodynamic (HEC-RAS 2D) and water quality model (WASP) for simulating flood-induced soil, sediment, and contaminant transport

Increased intensity and frequency of floods raise concerns about the release and transport of contaminated soil and sediment to and from rivers and streams. To model these processes during flooding events, we developed an External Coupler in Python to link the Hydrologic Engineering Center-River Analysis System (HEC-RAS) 2D hydrodynamic model to the Water Quality Analysis Simulation Program (WASP). Accurate data transfer from a hydrodynamic model to a water quality model is critical. Our test results showed the External Coupler successfully linked HEC-RAS and WASP and addressed technical challenges in aggregating flow data and conserving mass during the flood event. We ran the coupled models for a 100-year flood event to calculate flood-induced transport of sediment-associated arsenic in Woodbridge Creek, NJ. Change in surface sediment and arsenic at the end of 48-h flood simulation ranged from a net loss of 13.5 cm to a net gain of 11.6 cm, and 16.2 to 2.9 mg/kg, respectively, per model segment, which demonstrates the capability of the coupled model for simulating sediment and contaminant transport in flood.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

The development of laser-plasma interaction program LAP3D on thousands of processors

Modeling laser-plasma interaction (LPI) processes in real-size experiments scale is recognized as a challenging task. For explorering the influence of various instabilities in LPI processes, a three-dimensional laser and plasma code (LAP3D) has been developed, which includes filamentation, stimulated Brillouin backscattering (SBS), stimulated Raman backscattering (SRS), non-local heat transport and plasmas flow computation modules. In this program, a second-order upwind scheme is applied to solve the plasma equations which are represented by an Euler fluid model. Operator splitting method is used for solving the equations of the light wave propagation, where the Fast Fourier translation (FFT) is applied to compute the diffraction operator and the coordinate translations is used to solve the acoustic wave equation. The coupled terms of the different physics processes are computed by the second-order interpolations algorithm. In order to simulate the LPI processes in massively parallel computers well, several parallel techniques are used, such as the coupled parallel algorithm of FFT and fluid numerical computation, the load balance algorithm, and the data transfer algorithm. Now the phenomena of filamentation, SBS and SRS have been studied in low-density plasma successfully with LAP3D. Scalability of the program is demonstrated with a parallel efficiency above 50% on about ten thousand of processors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Investigating Accident Tolerant Fuel Concepts using the BISON Fuel Performance Code

There has been an increased interest in research of accident tolerant fuels (ATF) and claddings for use in commercial reactors ever since the events that occurred at the Fukushima Daiichi nuclear power plant in 2011. The economic impact of these events on the nuclear energy sector is significant. As a result, the United States Department of Energy's Office of Nuclear Energy accelerated research in nuclear fuel concepts with enhanced accident tolerance as part of its Fuel Cycle Research and Development (FCRD) Advanced Fuels Campaign (AFC). A report produced by the AFC entitled Light Water Reactor Accident Tolerant Fuel Performance Metrics outlines a set of metrics that can be used to guide selection of promising ATF concepts. Moreover, the report specifies that a down-selection is to occur in the 2016-2017 time frame, at which time the program will move from a proof-of-concept to a proof-of-principle stage with continued research and development into a small set of concepts. Given the time necessary for comprehensive irradiation experiments and post-irradiation examination, it is impossible to perform a complete set of experiments for material characterization. Therefore, the AFC is utilizing computational analysis tools in an effort to understand the proposed materials under a variety of normal operating and accident conditions. For some time, the DOE's Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has been developing computational analysis tools for nuclear fuel simulation. These codes include BISON and Marmot which investigate fuel behavior at the continuum and microstructural scales, respectively. In 2014, NEAMS introduced what it calls High Impact Problems (HIPs) into its program plan. These HIPs are intended to make significant advancements in a particular area of nuclear power research in a short period of time (3 years or less). NEAMS has chosen an ATF project, which emphasizes utilizing BISON and Marmot to model proposed materials, as its first HIP. This summary focuses on the methodology being utilized for investigation of ATF concepts using the BISON fuel performance code. First, we give an overview of the model development for two candidate ATF materials, FeCrAl for cladding and uranium silicide (U{sub 3}Si{sub 2}) for fuel. Then, we present the approach for deciding which simulations are necessary given the importance of such simulations in providing a detailed report into the fuel performance behavior of these materials by the conclusion of the HIP. In absence of experimental data and given the aggressive schedule outlined by the AFC for ATF research and development, computational analysis tools are required. These tools are being used to help guide experiment design and to perform bounding and sensitivity studies to gain valuable information for which experimental data is limited. In support of this effort, models have been incorporated into BISON for simulation of U{sub 3}Si{sub 2} and FeCrAl. Continued material model development and engineering analysis will help address questions related to the performance of these ATF materials under normal operating and accident conditions. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Comparison of Fission Product Release Predictions using PARFUME and BISON with Results from the AGR-3/4 Irradiation Experiment

The PARFUME (PARticle Fuel ModEl) fuel performance modeling code and the BISON nuclear fuel performance application built on the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element library were used to predict the fission product release from tristructural isotropic (TRISO) coated fuel particles and compacts during the third and fourth irradiation experiment of the Advanced Gas Reactor (AGR-3/4) Fuel Development and Qualification Program. The fuel performance modeling codes PARFUME and BISON modeled the AGR-3/4 irradiation experiment using the fuel compact time-averaged volume averaged (TAVA) daily temperatures for a total irradiation duration of 369.1 effective full power days (EFPD) to predict the release fraction of the fission product silver (Ag-110m) from a representative TRISO-coated fuel particle from AGR-3/4 compacts. Post-irradiation examination (PIE) measurements provided data on the release of these fission products in the compacts outside of the silicon carbide (SIC) layer. The PARFUME and BISON results were then compared to the silver release measured from compact gamma scanning. The results showed good agreement between PARFUME and BISON but both codes under-predicted the silver release fraction for all the compacts. In addition, BISON was used to model and predict the fission product concentration radial profile outside of the compacts in capsules’ inner and outer rings. These rings were either comprised of matrix and/or structural graphite. To obtain the concentration profiles of silver, cesium, and strontium, a sorption isotherm model was developed in BISON to capture the effects of fission product transport across the gaps between the concentric rings. The general shape of the concentration radial profiles as calculated by BISON were similar in the inner ring (IR) but varied in the outer ring (OR) depending on the fission product of interest or capsule temperature. Using this methodology and model, BISON now has the capability to aid in developing new fission product diffusion coefficients for matrix or structural graphite materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Empirical validation and comparison of methodologies to simulate micro and macro-encapsulated PCMs in the building envelope

Thermal Energy Storage (TES) has the potential to shift peak electricity demand. Passive TES is usually implemented in building envelope as micro and macro encapsulated phase change materials (PCM) to shift electric energy demand and therefore requires careful heat transfer analysis. Whole building energy modelling with simplified heat transfer analysis has become extremely important for designers, architects, engineers, and researchers to predict energy performance of buildings. It is important to validate PCM modelling algorithms used in building energy programs to quantify their error and prove their capacity to model different PCM encapsulation types. This study uses data from a microencapsulated PCM and two macroencapsulated PCMs (Bio based PCM and hydrate salts) tested in full-scale using the Advanced Multiscale Building Energy Research (AMBER) Lab located at the Colorado School of Mines and is used to validate a numerical algorithm written in MATLAB language. To approximate the heat transfer through a wall assembly with macroencapsulated PCM pouches, several modelling techniques that can reduce 3D heat transfer characteristics to 1D are explored in this research. A parallel path heat transfer modelling approach is found to give the closest agreement with the experimental data for the pouched PCMs in building envelope applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Simulation and Non-Simulation Based Human Reliability Analysis Approaches

Part of the U.S. Department of Energy’s Light Water Reactor Sustainability (LWRS) Program, the Risk-Informed Safety Margin Characterization (RISMC) Pathway develops approaches to estimating and managing safety margins. RISMC simulations pair deterministic plant physics models with probabilistic risk models. As human interactions are an essential element of plant risk, it is necessary to integrate human actions into the RISMC risk model. In this report, we review simulation-based and non-simulation-based human reliability assessment (HRA) methods. Chapter 2 surveys non-simulation-based HRA methods. Conventional HRA methods target static Probabilistic Risk Assessments for Level 1 events. These methods would require significant modification for use in dynamic simulation of Level 2 and Level 3 events. Chapter 3 is a review of human performance models. A variety of methods and models simulate dynamic human performance; however, most of these human performance models were developed outside the risk domain and have not been used for HRA. The exception is the ADS-IDAC model, which can be thought of as a virtual operator program. This model is resource-intensive but provides a detailed model of every operator action in a given scenario, along with models of numerous factors that can influence operator performance. Finally, Chapter 4 reviews the treatment of timing of operator actions in HRA methods. This chapter is an example of one of the critical gaps between existing HRA methods and the needs of dynamic HRA. This report summarizes the foundational information needed to develop a feasible approach to modeling human interactions in the RISMC simulations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Validation of Photovoltaic Modeling Tool HelioScope Against Measured Data

HelioScope is a cloud-based solar design software developed by Folsom Labs to model arrays based on physical design. Folsom Labs received a grant from the Department of Energy for the National Renewable Energy Laboratory to validate the performance of HelioScope's simulation engine against measured PV system performance. This study builds upon previous validation work by NREL of multiple other PV modeling tools, using the same fixed-tilt systems with available system specifications. HelioScope designs were set up using the same system specifications and concurrent weather data as were used in previous studies. The predicted performance results from the simulations were compared with measured data and to performance predictions by other PV modeling tools.

14 SOLAR ENERGY↗
DOE OSTI2017

Executive Summary to the AFC Regarding the NEAMS ATF HIP

The DOE through its Nuclear Energy Advanced Modeling and Simulation (NEAMS) program introduced so called High Impact Problems (HIPs). A HIP is intended to make significant advancements in a particular area of nuclear research in a short period of time (3 years or less). The first HIP selected by NEAMS was in the area of Accident Tolerant Fuels (ATF). The purpose of this executive summary is to compile the ATF materials investigated, computational models developed, and key findings of using the models in the engineering scale fuel code developed partially by NEAMS called BISON.

10 SYNTHETIC FUELS↗
DOE OSTI2020

BISON High Burnup Structure Modeling Capabilities Validated with a Selection of the Halden IFA-650 Rods

The U.S. Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS)program aims to develop predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON, a high-fidelity and high-resolution fuel performance tool at the engineering scale. This document continues analysis and refinement of capabilities added to BISON early this calendar year in regards to the incorporation of capabilities applicable to extended burnups in response to industry interest. Details are provided on high burnup thermal conductivity models, a refitting of the high-burnup structure (HBS) porosity formation model to include additional data, the coupling of the HBS volume fraction model to thermal conductivity and fine fragmentation models, and validation activities. The IFA-650.4 and IFA-650.9 loss of coolant accident (LOCA) analyses are revisited with the latest developments in this report. A new validation case, IFA-650.14 has also been added to the BISON test suite.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Analysis of xRAGE and flag high explosive burn models with PBX 9404 cylinder tests

High explosives are energetic materials that release their chemical energy in a short interval of time. They are able to generate extreme heat and pressure by a shock driven chemical decomposition reaction, which makes them valuable tools that must be understood. This study investigated the accuracy and performance of two Los Alamos National Laboratory hydrodynamic codes, which are used to determine the behavior of explosives within a variety of systems: xRAGE which utilizes an Eulerian mesh, and FLAG with utilizes a Lagrangian mesh. Various programmed and reactive burn models within both codes were tested using a copper cylinder expansion test. The test was based on a recent experimental setup which contained the plastic bonded explosive PBX 9404. Detonation velocity versus time curves for this explosive were obtained using Photon Doppler Velocimetry (PDV). The modeled results from each of the burn models tested were then compared to one another and to the experimental results. This study validate

36 MATERIALS SCIENCE↗
DOE OSTI2024

Optimal Electrification Using Renewable Energies: Microgrid Installation Model with Combined Mixture k-Means Clustering Algorithm, Mixed Integer Linear Programming, and Onsset Method

Optimal planning and design of microgrids are priorities in the electrification of off-grid areas. Indeed, in one of the Sustainable Development Goals (SDG 7), the UN recommends universal access to electricity for all at the lowest cost. Several optimization methods with different strategies have been proposed in the literature as ways to achieve this goal. This paper proposes a microgrid installation and planning model based on a combination of several techniques. The programming language Python 3.10 was used in conjunction with machine learning techniques such as unsupervised learning based on K-means clustering and deterministic optimization methods based on mixed linear programming. These methods were complemented by the open-source spatial method for optimal electrification planning: onsset. Four levels of study were carried out. The first level consisted of simulating the model obtained with a cluster, which is considered based on the elbow and k-means clustering method as a case study. The second level involved sizing the microgrid with a capacity of 40 kW and optimizing all the resources available on site. The example of the different resources in the Togo case was considered. At the third level, the work consisted of proposing an optimal connection model for the microgrid based on voltage stability constraints and considering, above all, the capacity limit of the source substation. Finally, the fourth level involved a planning study of electrification strategies based mainly on microgrids according to the study scenario. The results of the first level of study enabled us to obtain an optimal location for the centroid of the cluster under consideration, according to the different load positions of this cluster. Then, the results of the second level of study were used to highlight the optimal resources obtained and proposed by the optimization model formulated based on the various technology costs, such as investment, maintenance, and operating costs, which were based on the technical limits of the various technologies. In these results, solar systems account for 80% of the maximum load considered, compared to 7.5% for wind systems and 12.5% for battery systems. Next, an optimal microgrid connection model was proposed based on the constraints of a voltage stability limit estimated to be 10% of the maximum voltage drop. The results obtained for the third level of study enabled us to present selective results for load nodes in relation to the source station node. Finally, the last results made it possible to plan electrification using different network technologies and systems in the short and long term. The case study of Togo was taken into account. The various results obtained from the different techniques provide the necessary leads for a feasibility study for optimal electrification of off-grid areas using microgrid systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Advanced probabilistic risk analysis using RAVEN and RELAP-7

RAVEN, under the support of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program [1], is advancing its capability to perform statistical analyses of stochastic dynamic systems. This is aligned with its mission to provide the tools needed by the Risk Informed Safety Margin Characterization (RISMC) path-lead [2] under the Department Of Energy (DOE) Light Water Reactor Sustainability program [3]. In particular this task is focused on the synergetic development with the RELAP-7 [4] code to advance the state of the art on the safety analysis of nuclear power plants (NPP). The investigation of the probabilistic evolution of accident scenarios for a complex system such as a nuclear power plant is not a trivial challenge. The complexity of the system to be modeled leads to demanding computational requirements even to simulate one of the many possible evolutions of an accident scenario (tens of CPU/hour). At the same time, the probabilistic analysis requires thousands of runs to investigate outcomes characterized by low probability and severe consequence (tail problem). The milestone reported in June of 2013 [5] described the capability of RAVEN to implement complex control logic and provide an adequate support for the exploration of the probabilistic space using a Monte Carlo sampling strategy. Unfortunately the Monte Carlo approach is ineffective with a problem of this complexity. In the following year of development, the RAVEN code has been extended with more sophisticated sampling strategies (grids, Latin Hypercube, and adaptive sampling). This milestone report illustrates the effectiveness of those methodologies in performing the assessment of the probability of core damage following the onset of a Station Black Out (SBO) situation in a boiling water reactor (BWR). The first part of the report provides an overview of the available probabilistic analysis capabilities, ranging from the different types of distributions available, possible sampling strategies, and post processing analysis capabilities. The first part of the report provides an extensive description of two major developments introduced this year: adaptive sampling for limit surface sampling and multi variate distributions. The document concludes with a description of the demo case (BWR-SBO) and a discussion of the results obtained.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Advanced SAPHIRE 8 Modeling Methods for Probabilistic Risk Assessment via the Systems Analysis Program for Hands-On Integrated Reliability Evaluations (SAPHIRE) Software P-202

1.1. Overview of the Advanced SAPHIRE Material The Advanced SAPHIRE course material is intended to both (1) provide guidance for learning advanced SAPHIRE features during the class and (2) become a stand-alone reference document after finishing the class. Thus, the format for the class material is a combination of the traditional “overhead-type” of presentation information with a structured, reference-type document. Major topics that are covered in the Advanced SAPHIRE class include: Advanced data base concepts such as Model Type (e.g., random, seismic, fire, flood). Definition of house events and how they are used on a sequence-by-sequence basis to manipulate individual fault tree logic using sequence flag sets or fault tree flag sets. ? Basic event templates, compound basic event equation editors, and human error worksheets. A rule-based event tree top event substitution feature (called the Link Event Tree Rule Editor) which allows for top event substitutions. A rule-based cut set post-processing feature (called the Recovery Rules) which allows cut set manipulation. Cut set analysis based upon rule-based end state categories (called End State Analysis). Cut set generation options for both fault trees and event tree sequences. The large event tree methodology and how SAPHIRE can be used to generate sequence cut sets for this method. The transfer of data between SAPHIRE data bases and between other PRA codes (MAR-D).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Initial steady-state core simulation capability or thermal and pool-type molten salt reactors, coupling reactor physics, thermal-hydraulics, and evolving chemistry

This report presents the development and validation of an initial steady-state multiphysics capability for molten salt reactors (MSRs) under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in Fiscal Year 2025. The framework integrates neutronics, thermal-hydraulics, species transport, and thermochemistry to capture the coupled dynamics of liquid-fueled systems. Implementation and testing were performed on two representative designs: the Molten Salt Reactor Experiment (MSRE), a thermal-spectrum, channeled-flow reactor, and the Lotus Molten Salt Reactor (L-MSR), a fast-spectrum, pool-type reactor. The modeling suite employs Griffin for reactor physics and depletion, Pronghorn and SAM for thermal-hydraulics, Thermochimica for chemistry, and Saline for thermophysical properties, with benchmarking and validation carried out against historical MSRE data, experimental flow-loop measurements, and reference depletion calculations from Monte Carlo codes. The framework demonstrated the ability to reproduce key reactor behaviors including temperature feedback, reactivity losses, delayed neutron precursor transport, xenon poisoning, and redox potential evolution. The results confirm the feasibility and accuracy of the coupled models in predicting steady-state and selected transient MSR behaviors. This latter ones are used in this report as a proxy indicating that the steady-state models from which the transient starts are accurate. For MSRE, validation showed good agreement with pump start-up and natural circulation tests, while for the L-MSR, benchmarking confirmed hydraulic calibration and consistency of neutronics–thermal coupling. The tools also provided new insights into species transport, noble metal deposition, and salt solidification dynamics. On the Xenon transport front, the code is validated against the steady state Xenon poisoining measurement and showed good agreement with the experimental value. Identified areas for future work include advanced void transport modeling, three-dimensional simulations, improved alloy corrosion models, and tighter integration with high-fidelity Monte Carlo codes. These developments provide a foundation for high-fidelity MSR simulations that can support reactor design optimization, safety assessments, and long-term operational strategies.

42 - ENGINEERING↗
DOE OSTI2015

Experiments and Theoretical Data for Studying the Impact of Fission Yield Uncertainties on the Nuclear Fuel Cycle with TALYS/GEF and the Total Monte Carlo Method

We describe the research program of the nuclear reactions research group at Uppsala University concerning experimental and theoretical efforts to quantify and reduce nuclear data uncertainties relevant for the nuclear fuel cycle. We briefly describe the Total Monte Carlo (TMC) methodology and how it can be used to study fuel cycle and accident scenarios, and summarize our relevant experimental activities. Input from the latter is to be used to guide the nuclear models and constrain parameter space for TMC. The TMC method relies on the availability of good nuclear models. For this we use the TALYS code which is currently being extended to include the GEF model for the fission channel. We present results from TALYS-1.6 using different versions of GEF with both default and randomized input parameters and compare calculations with experimental data for {sup 234}U(n,f) in the fast energy range. These preliminary studies reveal some systematic differences between experimental data and calculations but give overall good and promising results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

The Virtual Test Bed (VTB) repository: a library of multiphysics reference reactor models using NEAMS tools

With the next generation of nuclear reactors under development, modeling and simulation (MS) tools are being developed by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in order to support their design, licensing, and future operation. Mirroring the physical test beds currently under construction (i.e., EBR-II and ZPPR), the Virtual Test Bed (VTB) was launched by the National Reactor Innovation Center (NRIC) in collaboration with NEAMS to support the advanced reactor community. This collaborative effort, which involves multiple teams at both Idaho National Laboratory and Argonne National Laboratory aims to use NEAMS tools to model a wide range of reactor designs. Those models are automatically tested to ensure their continued functionality as the tools are further developed. Examples are extensively documented, each acting as a tutorial for applying the relevant NEAMS tools to that reactor design. Currently, five advanced reactor types (with a total of eight specific design variants) are simulated by a variety of different models. These models range from steady-state, core multiphysics simulations to integrated plant analysis during loss-of flow transients. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

The Virtual Test Bed (VTB) Repository: A Library of Multiphysics Reference Reactor Models using NEAMS Tools

With the next generation of nuclear reactors under development, modeling and simulation (M&S) tools are being developed by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in order to support their design, licensing, and future operation. Mirroring the physical test beds currently under construction (i.e., EBR-II and ZPPR), the Virtual Test Bed (VTB) was launched by the National Reactor Innovation Center (NRIC) in collaboration with NEAMS to support the advanced reactor community. This collaborative effort, which involves multiple teams at both Idaho National Laboratory and Argonne National Laboratory aims to use NEAMS tools to model a wide range of reactor designs. Those models are automatically tested to ensure their continued functionality as the tools are further developed. Examples are extensively documented, each acting as a tutorial for applying the relevant NEAMS tools to that reactor design. Currently, five advanced reactor types (with a total of eight specific design variants) are simulated by a variety of different models. These models range from steady-state, core multiphysics simulations to integrated plant analysis during loss-of-flow transients.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Report in the Energy and Intensity Frontiers, and Theoretical at Northwestern University

The Northwestern (NU) Particle Physics (PP) group involved in this report is active on all the following priority areas: Energy and Intensity Frontiers. The group is lead by 2 full profs. in experimental physics (Schmitt and Velasco), 3 full profs. in theoretical physics (de Gouvea, Low and Petriello), and Heidi Schellman who is now at Oregon State. Low and Petriello hold joint appointments with the HEP Division at Argonne National Laboratory. The theoretical PP research focuses on different aspects of PP phenomenology. de Gouvea dedicates a large fraction of his research efforts to understanding the origin of neutrino masses, neutrino properties and uncovering other new phenomena, and investigating connections between neutrino physics and other aspects of PP. Low works on Higgs physics as well as new theories beyond the Standard Model. Petriello pursues a research program in precision QCD and its associated collider phenomenology. The main goal of this effort is to improve the Standard Model predictions for important LHC observables in order to enable discoveries of new physics. In recent years, the emphasis on experimental PP at NU has been in collider physics. NU expands its efforts in new directions in both the Intensity and the Cosmic Frontiers (not discussed in this report). In the Intensity Frontier, Schmitt has started a new effort on Mu2e. He was accepted as a collaborator in April 2015 and is identified with important projects. In the Energy Frontier, Hahn, Schmitt and Velasco continue to have a significant impact and expanded their CMS program to include R&D for the real-time L1 tracking trigger and the high granularity calorimeter needed for the high-luminosity LHC. Hahn is supported by an independent DOE Career Award and his work will not be discussed in this document. The NU analysis effort includes searches for rare and forbidden decays of the Higgs bosons, Z boson, top quark, dark matter and other physics beyond the standard model topics. Four students completed their PhD: Kubik is now contributing to the Cosmic Frontier program, Pollack to both the Intensity and Energy Frontiers and Pozdnyakov and Odell will continue in the Energy Frontier. All our research scientists, Anastassov, Oferzynski, Lusito, and Stoynev, have found new positions. The new post-docs are Trovato from Scuola Normale de Pisa, Odell from Northwestern and Bhattacharya from Brown. Trovato is now supported by Hahn, and so is Sung, previously at MIT.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗