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At least 37 records · Page 2

Magnetic structure of Fe 16 N 2 determined by polarized neutron diffraction on thin-film samples

Strain-free Fe 16 N 2 thin films were obtained on MgO (001) single-crystal substrates with Cr seed layers. Additionally, x-ray diffraction and transmission electron microscopy confirmed that the film is textured in all three spatial directions with crystallographic orientation determined by epitaxial constraints from the substrate. Average grain size was estimated to be in the range of tens of nanometers. Ten pieces of 40-nm-thick Fe 16 N 2 thin-film samples were stacked together for half-polarized neutron diffraction study at room temperature. A total of six reflections were usable, from which the magnetic structure of Fe 16 N 2 was determined and compared to existing models. Contrary to most electronic structure calculations, the present results suggest that the magnetic moment of Fe atoms at the 8h site is large and larger than that of the 4d site. Our results support the giant magnetization of Fe 16 N 2 .

36 MATERIALS SCIENCE↗

A data mining approach to investigate food groups related to incidence of bladder cancer in the BLadder cancer Epidemiology and Nutritional Determinants International Study

Abstract At present, analysis of diet and bladder cancer (BC) is mostly based on the intake of individual foods. The examination of food combinations provides a scope to deal with the complexity and unpredictability of the diet and aims to overcome the limitations of the study of nutrients and foods in isolation. This article aims to demonstrate the usability of supervised data mining methods to extract the food groups related to BC. In order to derive key food groups associated with BC risk, we applied the data mining technique C5.0 with 10-fold cross-validation in the BLadder cancer Epidemiology and Nutritional Determinants study, including data from eighteen case–control and one nested case–cohort study, compromising 8320 BC cases out of 31 551 participants. Dietary data, on the eleven main food groups of the Eurocode 2 Core classification codebook, and relevant non-diet data (i.e. sex, age and smoking status) were available. Primarily, five key food groups were extracted; in order of importance, beverages (non-milk); grains and grain products; vegetables and vegetable products; fats, oils and their products; meats and meat products were associated with BC risk. Since these food groups are corresponded with previously proposed BC-related dietary factors, data mining seems to be a promising technique in the field of nutritional epidemiology and deserves further examination.

Nutrition & Dietetics↗

Improving bamboo’s fuel and storage properties with a net energy export through torrefaction paired with catalytic oxidation

Using torrefied char, or biocoal, as solid fuel provides an opportunity to introduce a sustainable feedstock into the energy market. The goals of this study were to investigate how torrefaction improves the energy content and the grindability of a Malaysian bamboo along with understanding the potential for integrated energy recovery from torrefaction gases. The feedstock was torrefied at 250–290 °C for 1 h and the combustion characteristics and grindability of the solid products along with the composition of torrefied gas species were measured. The results showed a beneficial increase in elemental carbon increased from 47 to 63 wt% at 290 °C torrefaction, reflecting an increase in higher heating value from 17.8 to 25.6 MJ/kg. The combustion behavior of all the products appeared to show three distinct combustion zones; however, torrefaction severity leading to higher combustion temperature and time as the fixed carbon augmented with the increase of torrefaction temperature. This increase in severity also lead to more friable and grindable material, and the 290 °C condition required a factor of 2.7 less hold-up time in the mill compared to the raw bamboo, and a factor of 8.5 less energy (938 and 111 kWh/tonne respectively). Through analysis of the gas and volatile formation, a case study showed that catalytic oxidation can convert nearly 100% of the embodied chemical energy into usable thermal energy. These experimental findings were scaled to a 100,000 tonne/y capacity torrefaction plant and in the moderate case of 270 °C operating temperature, the plant has 1.25 GJ/tonne excess energy beyond what the process needs.

09 BIOMASS FUELS↗

An Assessment of the Usability of Machine Learning Based Tools for the Security Operations Center

Gartner, a large research and advisory company, anticipates that by 2024 80% of security operation centers (SOCs) will use machine learning (ML) based solutions to enhance their operations. 1 1 https://www.ciodive.com/news/how-data-science-tools-can-lighten-the-load-for-cybersecurity-teams/572209/ In light of such widespread adoption, it is vital for the research community to identify and address usability concerns. This work presents the results of the first in situ usability assessment of ML-based tools. With the support of the US Navy, we leveraged the national cyber range-a large, air-gapped cyber testbed equipped with state-of-the-art network and user emulation capabilities-to study six US Naval SOC analysts' usage of two tools. Our analysis identified several serious usability issues, including multiple violations of established usability heuristics for user interface design. We also discovered that analysts lacked a clear mental model of how these tools generate scores, resulting in mistrust a and/or misuse of the tools themselves. Surprisingly, we found no correlation between analysts' level of education or years of experience and their performance with either tool, suggesting that other factors such as prior background knowledge or personality play a significant role in ML-based tool usage. Our findings demonstrate that ML-based security tool vendors must put a renewed focus on working with analysts, both experienced and inexperienced, to ensure that their systems are usable and useful in real-world security operations settings.

Oesch, T↗

Postmortem and Antemortem Forensic Assessment of Pediatric Fracture Healing from Radiographs and Machine Learning Classification

A timeline of pediatric bone healing using fracture healing characteristics that can be assessed solely using radiographs would be practical for forensic casework, where the fracture event may precede death by days, months, or years. However, the dating of fractures from radiographs is difficult, imprecise, and lacks consensus, as only a few aspects of the healing process are visible on radiographs. Multiple studies in both the clinical and forensic literature have attempted to develop a usable scale to assess pediatric bone healing on radiographs using various healing characteristics. In contrast to the orthopedic definition, a fracture in forensic casework is only considered to be healed when the area around the fracture has been remodeled to the point that the fracture is difficult to detect on a radiograph or on the surface of the bone itself, a process that can take several years. We subjectively assessed visible characteristics of healing in radiograms of fractures occurring in 942 living children and adolescents. By dividing these assessments into learning and test (validation) sets, the accuracy of a newly proposed fracture healing scale was compared to a previous study. Two machine learning models were used to test predictions of the new scale. All three models produced similar estimates with substantial imprecision. Results corroborate the Malone model with an independent dataset and support the efficacy of using less complex models to estimate fracture age in children.

60 APPLIED LIFE SCIENCES↗

Investigating Scientific Data Change with User Research Methods

Scientific datasets are continually expanding and changing due to fluctuations with instruments, quality assessment and quality control processes, and modifications to software pipelines. Datasets include minimal information about these changes or their effects requiring scientists manually assess modifications through a number of labor intensive and ad-hoc steps. The Deduce project is investigating data change to develop metrics, methods, and tools that will help scientists systematically identify and make decisions around data changes. Currently, there is a lack of understanding, and common practices, for identifying and evaluating changes in datasets since systematically measuring and managing data change is under explored in scientific work. We are conducting user research to address this need by exploring scientist's conceptualizations, behaviors, needs, and motivations when dealing with changing datasets. Our user research utilizes multiple methods to produce foundational, generative insights and evaluate research products produced by our team. In this paper, we detail our user research process and outline our findings about data change that emerge from our studies. Our work illustrates how scientific software teams can push beyond just usability testing user interfaces or tools to better probe the underlying ideas they are developing solutions to address.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

ExaCA v2.0: A versatile, scalable, and performance portable cellular automata application for additive manufacturing solidification

The previously established ExaCA software for performance portable alloy grain structure simulation has been updated to better represent the solidification behavior during complex alloy processing conditions, such as those encountered during metal additive manufacturing (AM), and for improved performance and scalability. Here, an extension to the time–temperature history input data format and the core ExaCA algorithm to include an arbitrary number of melting and solidification events yielded improved prediction of texture for various melt pool geometries, expanding the range of AM-relevant conditions that can be accurately simulated. Improved heat transport process simulation coupling, including the creation of large raster datasets from single track time–temperature history data and in-memory coupling with the new, performance portable finite difference code Finch, were also demonstrated in example studies on the effect of multilayer AM microstructure predictions on hatch spacing and cell size, respectively. Additional new features are detailed and demonstrated, including the ability to perform simulations using various interfacial response function forms, execute simulations on state-of-the-art hardware, improved usability through post-processing versatility, and improved strong and weak scaling performance. The performance, physics, and versatility improvements demonstrated here will further enable large-scale studies on AM process–microstructure relationships that were not previously possible. Furthermore, the usability improvements and ability to run coupled AM process–microstructure simulations using the Finch-ExaCA workflow will facilitate broader use of this open-source software by the computational materials community.

36 MATERIALS SCIENCE↗

Mapping O 2 concentration in ex-vivo tissue samples on a fast PLIM macro-imager

O 2 PLIM microscopy was employed in various studies, however current platforms have limitations in sensitivity, image acquisition speed, accuracy and general usability. We describe a new PLIM imager based on the Timepix3 camera (Tpx3cam) and its application for imaging of O 2 concentration in various tissue samples stained with a nanoparticle based probe, NanO 2 -IR. Upon passive staining of mouse brain, lung or intestinal tissue surface with minute quantities of NanO 2 -IR or by microinjecting the probe into the lumen of small or large intestine fragments, robust phosphorescence intensity and lifetime signals were produced, which allow mapping of O 2 in the tissue within 20 s. Inhibition of tissue respiration or limitation of O 2 diffusion to tissue produced the anticipated increases or decreases in O 2 levels, respectively. The difference in O 2 concentration between the colonic lumen and air-exposed serosal surface was around 140 µM. Furthermore, subcutaneous injection of 5 µg of the probe in intact organs (a paw or tail of sacrificed mice) enabled efficient O 2 imaging at tissue depths of up to 0.5 mm. Overall, the PLIM imager holds promise for metabolic imaging studies with various ex vivo models of animal tissue, and also for use in live animals.

59 BASIC BIOLOGICAL SCIENCES↗

Magnetic Weyl Semimetallic Phase in Thin Films of Eu 2 Ir 2 O 7

The interplay between electronic interactions and strong spin-orbit coupling is expected to create a plethora of fascinating correlated topological states of quantum matter. Of particular interest are magnetic Weyl semimetals originally proposed in the pyrochlore iridates, which are only expected to reveal their topological nature in thin film form. To date, however, direct experimental demonstrations of these exotic phases remain elusive, due to the lack of usable single crystals and the insufficient quality of available films. Here, in this study, we report on the discovery of signatures for the long-sought magnetic Weyl semimetallic phase in (111)-oriented Eu 2 Ir 2 O 7 high-quality epitaxial thin films. We observed an intrinsic anomalous Hall effect with colossal coercivity but vanishing net magnetization, which emerges right below the onset of a peculiar magnetic phase with all-in-all-out (AIAO) antiferromagnetic ordering. The anomalous Hall conductivity obtained experimentally is consistent with the theoretical prediction, likely arising from the nonzero Berry curvature emanated by Weyl node pairs near the Fermi level that act as sources and sinks of Berry flux, activated by broken cubic crystal symmetry at the top and bottom terminations of the thin film.

36 MATERIALS SCIENCE↗

Metal oxide supported Ni-impregnated bifunctional catalysts for controlling char formation and maximizing energy recovery during catalytic hydrothermal liquefaction of food waste

Nickel (Ni)-impregnated metal oxide catalysts, Ni/CeZrO x , Ni/ZrO 2 , and Ni/CeO 2 , were investigated to maximize energy recovery and reduce char yield during catalytic hydrothermal liquefaction (CHTL) of food waste. Yields of char, biocrude, water soluble products, and gas were measured at 300 °C and 1 hour for both the parent oxides (CeZrO x , ZrO 2 , and CeO 2 ) and the Ni-impregnated versions. Using Ni-based catalysts reduced the carbon-weighted char yield from 16–24% to <10% and decreased the energy recovery of char from 39–47% to <21%, as compared with control tests. In particular, using Ni/ZrO 2 resulted in the greatest biocrude yield, greatest reduction of char yield, and greatest energy recovered as biocrude (39.2%). After factoring in all forms of usable energy produced from food waste, the total energy recovery obtained for the catalysts studied here was >60%. Ni/ZrO 2 and Ni/CeO 2 show the greatest potential for controlling char growth and maximizing energy recovered from food waste. The crystalline structures of all three oxides were hydrothermally stable. Catalyst reuse tests indicate that the biocrude and char yields remained the same for the first and second use (within uncertainty) and that the catalyst retains its initial crystallinity and 93% of its initial Ni content. Molecular composition of biocrudes analyzed by the state-of-the-art analytical platforms (including GC-MS, GC × GC, FT-ICR MS, and 1H NMR) revealed minor differences in the chemical constituents of biocrudes obtained using different catalysts and provided some insight regarding reaction mechanism.

09 BIOMASS FUELS↗

A Design of Activity-Based Mobility Intervention

Human mobility influences our society and vice versa. During the COVID-19 pandemic, non-pharmaceutical intervention that alters activity-based mobility such as work-from-home greatly impacted human mobility patterns. Many studies on developing mitigation strategies have employed or implemented their own mobility intervention within their model assumption. For fair evaluation between intervention strategies across models, it is significant to set up compatible experimental environments. However, it is difficult to apply the identical intervention to different kinds of models and compare their effectiveness because each model might have different assumptions, capabilities, and implementations. Even if one can apply intervention to heterogeneous models, it may produce undesirable artifacts due to difference of models and integration with intervention. Therefore, minimizing undesirable artifacts and facilitating intervention experiments across heterogeneous models are substantial. Taking this into account, this paper investigates a design of activity-based mobility intervention (ABMI). We define ABMI together with related concepts and develop an extensible data model and schema of ABMI based on the 5W1H method that can be used in different models. As a case study, we apply the ABMI model to a micro-simulation to demonstrate the usability of the proposed model. We expect that standardized ABMI and interfaces may help to streamline development and experiments of intervention strategies across heterogeneous models.

Kim, Joon-Seok↗

Methods and Usability Enhancements in Shift for Non-LWR Applications

Several development and analysis tasks were undertaken in FY21 under the Nuclear Energy Advanced Modeling and Simulation program to enhance modeling of non light–water reactors (LWRs) with Shift. Specifically, these efforts targeted enhancements for tristructural isotropic (TRISO) fuel modeling. A new Shift user interface was developed that allows for much better usability and ease of modeling for non-LWR problems and TRISO fuel. Performance studies were conducted using an HTR-10 fuel pebble model by comparing different geometry packages in Shift, KENO-VI, and Serpent. These studies showed that the new geometry package in Shift performs well compared to Serpent for TRISO fuel modeling with consistent tracking options between both packages. The studies also identified the most critical areas of improvement for more efficiently performing Monte Carlo transport on TRISO fuel models with Shift. Tally calculations in Shift were optimized for non-LWR cross section generation and depletion calculations, and areas for further optimization and accuracy improvements were identified. Finally, initial collaboration efforts were formed between Idaho National Laboratory, Argonne National Laboratory, and the Nuclear Regulatory Commission to use Shift for Comprehensive Reactor Analysis Bundle support.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Modeling graphene sheet growth and dynamical matrix calculations using molecular dynamics

Molecular dynamics (MD) has been an incredibly useful tool to model physical processes that were synthesized experimentally but not fully understood. MD, through the use of semi-empirical inter-atomic potentials, has allowed understanding of different physical processes in materials science. Yet as well as providing useful insights into materials science, molecular dynamics has a wider range of usability. In this report, I will be detailing how MD can be used to study graphene formation from a carbon liquid which requires high temperatures and pressures. Beyond this, I will describe the usefulness of MD for understanding the physics for phonon transport quantum sensors. To do this, MD was employed to determine the dynamical matrix by treating atoms as coupled oscillators. An accurate understanding of the dynamical matrix of a system is required to calculate the non-equilibrium Green’s function used to describe the phonon transport within phonon wave-guides. I found that, across multiple pressures and temperatures, randomly placed carbon atoms will show evidence of pent-first formation with semi-empirical models. Density functional theory (DFT), on the other hand, was too computationally expensive to use for full scale MD simulations, but we have the possibility of training a machine learned interatomic potential to approximate DFT for carbon in the environments being studied for pent-first graphene sheet formation.

36 MATERIALS SCIENCE↗

The Study of TRR Radial Thermal Shielding Dismantling Process - 20063

The decommissioning of nuclear facilities has become an important worldwide topic because many nuclear power facilities will permanently cease operation in the foreseeable future. Taiwan Research Reactor (TRR) has stepped into the decommissioning phase in 2004, and the dismantling processes will start in 2022. TRR is a heavy water reactor designed by Canatom Company with output thermal power 40 MW. On January 3, 1973, it reaches criticality. TRR had been operated for 15 years and was permanently shut down in early 1988. The decommissioning plan of TRR was approved in 2004. According to the Nuclear Reactor Facilities Regulation Act in Taiwan, a nuclear facility must be dismantled in 25 years after stepping into the decommissioning phase. Therefore, TRR decommissioning must be completed before 2029. One of the most important tasks of TRR decommissioning is to dismantle reactor body. In the task of TRR decommissioning, mechanical cutting with remote handling is used to dismantle radial thermal shielding, which are the internal components of the TRR. This study outlines the internal components of the TRR and explains the difficulties encountered during the dismantling processes. Considering the structure and radiation dose rate of TRR and its internal components, the dismantling method and packaging method are properly arranged to complete the TRR dismantling task. This study describes the process of dismantling the radial thermal shielding during the dismantling processes and considers the impact of the radiation dose on the staff during the operation. The calculation of the radiation dose rate for the personnel during the segmentation process is based on the evaluation result by using VRdose. If the calculation of personnel working dose rate is too high, we will increase the shielding or use remote handling to reduce the operator's exposure dose in the dismantling processes to comply with the As Low As Reasonably Achievable (ALARA) principle. In this study, the latest developments in the TRR decommissioning program are described. It also provides usable experience and information regarding the future decommissioning of other nuclear facilities or nuclear power plants in Taiwan. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Recycling Disassembled Automotive Plastic Components for New Vehicle Components: Enabling the Automotive Circular Economy

As the automotive industry increasingly relies on plastic components to meet fuel efficiency and emissions targets, the challenge of managing end-of-life vehicle (ELV) plastics continues to grow. Currently, more than 80% of ELV plastics in the U.S. are landfilled due to limited economic incentives and technical barriers to recycling. This study examines a mechanical recycling pathway for thermoplastic components disassembled from ELVs and assesses their usability for reintegration into new vehicle parts. Four representative materials were chosen based on material labels embedded in recovered parts and aligned with their virgin industrial equivalents: polypropylene (PP), 10% talc-filled PP (PP-T10), 20% talc-filled PP (PP-T20), and a 20% glass-/mineral-filled polyamide (PA6 + GF7 + MF13). The materials underwent shredding, drying, and injection molding before being characterized by particle size analysis, density measurement, thermal analysis (TGA, DSC), mechanical testing, and heat deflection temperature (HDT) evaluation. The results in this work indicated that minor differences in crystallinity were observed and small differences between model materials and ELV materials could have contributed to these changes. Mechanical testing revealed that neat polypropylene suffered a 15–20% reduction in stiffness and tensile strength, but talc-filled polypropylene and glass/mineral-filled nylon retained >90% of their modulus, strength, and heat deflection temperature values relative to virgin controls. Differences between virgin and ELV materials could have been attributed to use life degradation, contamination during use life, or even chemical/processing differences in model materials and ELV materials. However, these findings suggest that mechanically recycled, disassembled ELV plastics can retain sufficient structural performance to support circularity efforts in the automotive sector.

automotive recycling↗

Connecting Nitrogen Transformations Mediated by the Rhizosphere Microbiome to Perennial Cropping System Productivity in Marginal Lands

The demand for energy from biofuel production is increasing, prompting concerns about the environmental impact and long-term sustainability of bioenergy cropping systems. These cropping systems will make up much of our future landscapes, and threaten to take the place of food cropping systems. Many life cycle analyses of bioenergy sustainability focus on carbon accrual and budgets, since they want to maximize carbon accrual while producing alternative fuel. Less attention has been given to nitrogen (N) dynamics in these systems. N is the most commonly limiting nutrient for plants, but applying nitrogen fertilizer- as we do for most cropping systems – is harmful to the environment, energetically costly, and produces greenhouse gases. In other words, adding nitrogen by fertilizer bioenergy systems could add to the very problems (climate change) it is trying to address. This is especially true for the areas that are proposed for bioenergy systems: marginal lands. These more degraded lands do not complete with food crops, but do have limited nitrogen. If we are to use these marginal lands for bioenergy, we need to understand the mechanisms regulating nutrient acquisition, and identify ways that bioenergy crops can get nitrogen in sustainable ways. Nutrient acquisition in the soil is performed by microbes in the root zone, or rhizosphere. Microbes can either mineralize nitrogen in the soil (from organic forms) or fix nitrogen from the air, in a process called nitrogen fixation. The goal of our project was thus to understand how the rhizosphere microbiome provides nutrients to bioenergy crops on marginal lands. We focus especially on the process of nitrogen fixation, since it has potential to get “fertilizer for free” that has much less environmental harm. We investigated this goal using sites from the DOE Great Lakes Bioenergy Research Center (GLBRC) in the upper Midwest, and associated lab and ‘omics methods. We group our findings into three major areas. First, we showed that nitrogen fixation, the conversion of N2 gas from the air to ammonium that is usable by plants, is performed in bioenergy soils, and benefits switchgrass crops. While more well-studied in leguminous plants, free-living nitrogen fixation can occur in some systems, and represents a potential opportunity to gain ‘free’ sustainable nitrogen source. We identified the nitrogen fixing bacteria that were most active in providing switchgrass with N, and showed that the drivers of nitrogen fixation occurred at a microscale; it is not well-predicted by bulk variables like soil moisture or plant phenology. Second, we showed that nitrogen fixation is not suppressed by long-term fertilizer. We expected that plentiful nitrogen would reduce the symbiotic relationship between nitrogen fixers and plants, and ‘downregulate’ fixation. We did not find evidence for this, either after long-term fertilizer in the field, or short-term fertilizer in the greenhouse. Finally, we identified the root exudates, carbon compounds that are emitted from the root, that best stimulate nitrogen fixation. We found that carbohydrates were better at stimulating fixation than organic acids. We expected these exudates to be emitted from the plant in periods of high N demand, but we found they are emitted when N is plentiful. This suggests that the stimulation of N fixation by plants is a passive process. Overall, we show that nitrogen fixation has potential to support bioenergy cropping system, and future management could develop ways to maximize it. However, this may not be best achieved via the plant – we found very little evidence of a ‘transactional’ system by which plants are controlling when and where nitrogen fixation is stimulated. It will be better to understand how management practices like planting and fertilizer application affect the microscale soil dynamics, which will determine nitrogen fixation rates.

59 BASIC BIOLOGICAL SCIENCES↗

Advancing material modeling in hydrocodes using a concurrent finite-element and molecular dynamics multiscale framework

We present a multiscale simulation framework that couples the finite-element method with molecular dynamics. Bypassing traditional equations of state (EOS) by using in-line atomistic simulations, the method offers the advantage of incorporating detailed microscale physics not easily represented with coarse-grained models. Coupling consistency with the continuum code is ensured through the use of lifting and restriction operators, in line with heterogeneous multiscale methods. The concurrent continuum-atomistic framework is validated through comparison with experimental results and conventional EOS models, and demonstrated in a shock-driven hydrodynamic flow simulation under extreme conditions. We further evaluate the framework's usability by comparing it to state-of-the-art EOS models of deuterium. A computational performance study reveals that the atomistic EOS evaluation is a feasible alternative to conventional approaches, and demonstrates a weak scaling of 99% efficiency. These results highlight the framework's potential for large-scale multiscale modeling across a broad range of materials and conditions.

Computer science↗

Baylor University Campus-Wide Deep Dive

In January 2020, staff members from the Engagement and Performance Operations Center (EPOC) and the Lonestar Education And Research Network (LEARN) met with researchers and staff at Baylor University for the purpose of a Campus-Wide Deep Dive into research drivers. The goal of this meeting was to help characterize the requirements for five campus research use cases and to enable cyberinfrastructure support staff to better understand the needs of the researchers they support. Profiled scientific use cases included: - Experimental High Energy Physics (HEP) - Proton Computed Tomography (pCT) - Nutrition and Relation to Digestive Microbiome - Baylor University Core Research Facilities - Molecular Quantum-dot Cellular Automata (QCA), and Material Science of Quantum Computing - Modeling and Simulation of Low-Dimensional and Nano-Structured Materials - Computational Fluid Dynamics Material for this event included the written documentation from each of the research areas at Baylor University, documentation about the current state of technology support, and a write-up of the discussion that took place in person. The Case Studies highlighted the ongoing challenges that Baylor University has in supporting a cross-section of established and emerging research use cases. Each Case Study mentioned unique challenges which were summarized into common needs. These included: - Tradeoffs for network/software security, and usability of the resulting infrastructure. Better communication to set expectations and understand realities is required. - Computation use on campus is widespread and healthy. While no major problems were uncovered, upgrades to maintain current usage patterns and encourage growth will be required. - Storage is a critical need for enterprise use cases and research. In particular, a campus wide ‘storage architecture’ to support research use cases (e.g. instruments, data sharing) is required in the 2-5 year time window. - Instrumentation on campus is healthy and expanding. Technology must scale with this in the form of computation and storage. - Working with LEARN to upgrade network capacity (in multiples of 10G, or upgrades to 100G) will be required in the 1-3 year time frame. - Network monitoring and visibility will help to establish external science use cases. - Data sharing via portal systems is not currently a critical need, but growing in scope. EPOC can assist Baylor with options.

99 GENERAL AND MISCELLANEOUS↗