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At least 109 records · Page 6

Durability Evaluation of Advanced Fenestration Technologies

In the U.S., more than 40% of primary energy and 70% of electricity is consumed in residential and commercial buildings, resulting in annual energy costs of more than $430 billion. Approximately 35% of this consumption can be attributed to losses through the building envelope, of which windows are currently the weakest link. Multiple technologies are under development to improve this performance. This includes dynamic and photovoltaic glazing as well as emerging highly insulating technologies including vacuum insulating glass (VIG), aerogels and thin-glass based multi-pane configurations. While windows are specified based on expected performance as installed, the energy savings realized by high performance windows are delivered over time. This makes it critical to understand and maximize the durability of high-performance windows to ensure those projected energy savings are delivered. Present methods for evaluating durability are based on existing technologies. These methods may not apply or be adequate for newer emerging technologies which often present novel failure mechanisms that need to be understood and evaluated differently. In this presentation, we will discuss our efforts to define appropriate methods to improve the evaluation of many existing technologies as well as evaluate the durability of emerging window technologies. This work results from the combination of an extensive review of various international standards as well as existing scientific literature. In addition, input was gathered from multiple industry stakeholders regarding present practice as well as feedback on proposed improvements to existing methods. Here we will share these findings and present proposed improvements to developing and existing durability evaluation protocols.

building envelope↗

Search for third-generation vector-like leptons in $pp$ collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for vector-like leptons in multilepton (two, three, or four-or-more electrons plus muons) final states with zero or more hadronic $τ$-lepton decays is presented. The search is performed using a dataset corresponding to an integrated luminosity of 139 fb -1 of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded by the ATLAS detector at the LHC. To maximize the separation of signal and background, a machine-learning classifier is used. No excess of events is observed beyond the Standard Model expectation. Using a doublet vector-like lepton model, vector-like leptons coupling to third-generation Standard Model leptons are excluded in the mass range from 130 GeV to 900 GeV at the 95% confidence level, while the highest excluded mass is expected to be 970 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Multistage Condensation Pathway Minimizes Hysteresis in Water Harvesting with Large-Pore Metal–Organic Frameworks

Metal-organic frameworks (MOFs) have emerged as promising materials for atmospheric water harvesting (AWH). Large-pore MOFs provide high water capacity, but their significant hysteresis between sorption and desorption makes them unsuitable for AWH. Co2Cl2(BTDD) is a noteworthy exception. This MOF has large, 2.2 nm diameter one-dimensional pores, and combines both record-high water capacity and minimal hysteresis, making it an excellent material for water capture in arid areas. Sorption reversibility in Co2Cl2(BTDD) has been attributed to continuous water uptake. However, the sharp adsorption/desorption in the isotherms supports a discontinuous first-order transition. Here we use molecular simulations to compute the water adsorption and desorption pathways and isotherms in a Co2Cl2(BTDD) model, to elucidate how does this MOF achieve reversibility despite its large pore size. The simulations reveal a multi-stage mechanism of discontinuous water uptake facilitated by spatial segregation of rows of hydrophilic metal sites bridged by ~1 nm hydrophobic ligands. The multi-stage mechanism breaks the barrier of capillary condensation into smaller, easier to surmount ones, resulting in a facile process despite the sharp density discontinuity between confined liquid and vapor. Our results explain why exchanging Co2+ for Ni2+ or Clfor F- in the MOF have minimal impact on the condensation and desorption pressures. On the other hand, we predict that a decrease in hydrophilicity of the MOF vertices would strongly increase the hysteresis. We expect that the relationships between spatial distribution of hydrophilic sites and hysteresis unraveled in this study assist the design of water harvesting materials with maximal capacity and reversibility.

Zaragoza, Alberto↗

LCOE reduction through proactively optimized monitoring of PV Systems (Final Technical Report)

The project demonstrates the value proposition for a high-resolution monitoring system (HRMS) with diagnostic-prognostic capability and determine its impact on LCOE. The HRMS differs from conventional monitoring systems in a number of ways. First it will include the capability to automatically measure IV curves at the string and module levels. This provides a much richer view into the DC performance of the PV system and allows classification of many typical failure and degradation modes. Second, it will incorporate software capable of quantifying power and energy losses in the field as well as define the location and mechanism of the power and energy loss. Moreover, we aimed to deliver a prognostic system that is capable of predicting certain failures before they occur and giving system operators the opportunity to more efficiently plan operations and maintenance (O&M) activity in order to lower costs and increase yield over the life of the system. The research identifies cost targets required for different monitoring stages, including at the string combiner, at the individual string, and at the module level, to lower the levelized cost of energy (LCOE). Finally, a comprehensive guide determines the value PV monitoring brings to PV field operations. The guide assists plant operators in maximizing value from existing plants and identify the trade-offs of different monitoring solutions for future plants depending on the size, location, and expected system lifetime.

14 SOLAR ENERGY↗

Optimal scheduling for profit maximization of energy storage merchants considering market impact based on dynamic programming

This paper analyzes how electricity merchants' market impact affects merchants' profit. Energy storage has long been studied for its role in maximizing profit, and merchant decisions are assumed to have no impact on market prices. However, the trading decisions of large-scale energy storage merchants (e.g., pumped storage hydro) will affect the market prices. This paper employs dynamic programming theory to investigate merchants' optimal economic dispatch considering the market impact and physical characteristics of storage systems. Our findings show that the State-of-Charge (SOC) based analytical solution significantly facilitates energy storage merchants' decision-making. The SOC range is segmented into three regions by two optimal SOC reference points, which depend on the available energy in storage, given prices, and market impact. By comparing the current storage SOC with the reference points, the merchant can get the corresponding optimal actions. We analytically show that if the merchant neglects the market impact on the power market, she will exaggerate her expected profit when the price-taker and price-maker merchants have the same generating and pumping upper limits offered to Independent System Operators (ISOs). Furthermore, the profit-maximizing merchant must, therefore, assay to balance the trade-off correctly between the intensity of market impact and the dispatched power. Our findings are verified by numerical simulation, and results demonstrate the ramifications for electricity merchants in energy arbitrage decisions.

25 ENERGY STORAGE↗

High-Level Synthesis of Irregular Applications: A Case Study on Influence Maximization

The Influence Maximization problem is the problem of identifying a small cohort of actors from a broader population that, when initially activated in a diffusion process, are expected to result in a large number of activations in the population. While the problem is known to be NP-hard, several approximation algorithms have been devised by leveraging its submodular structure. While these algorithms are theoretically efficient, they are computationally very expensive in practice. This work advances the current state-of-the-art parallelization scheme for the IMM algorithm by devising the adoption of custom hardware accelerators implemented on FPGAs by leveraging High Level Synthesis from OpenCL. We study the performance of our proposed approach by exploring optimizations tailored at improving the parallel efficiency of the accelerators and highlight their effects and limitations in accelerating complex graph analytic applications. Our experimental evaluation shows that FPGA acceleration can improve the performance of the LT diffusion model up to 1.72x for the entire application and up to 2.90x for its most important kernel with respect to a CPU only parallel execution. The FPGA acceleration of the LT model shows also a 1.54x reduction in energy consumption when compared to a parallel CPU only run.

Neff, Reece W.↗

Assessing the New Home Market Opportunity: Case Study and Cost Modeling for Solar and Storage in 2030

Residential solar and storage markets are growing in the United States. With approximately 1 million new homes constructed every year, this represents a significant opportunity for solar and storage installations. Some homebuilders have begun to build new homes with solar and storage included as a standard offering. It is not clear how solar and storage is incorporated into the new construction process and at what cost. Further, it is unclear what barriers or opportunities exist to scale this model nationwide. To fill this gap in the literature, this research conducts a case study of Mandalay Homes' new solar and storage community in Arizona to gather lessons learned. From this foundation, we further generate a set of pathways to reduce install costs and expand solar and storage market penetration in this sector. To model existing and 2030 solar and storage costs, we use the National Renewable Energy Laboratory's (NREL's) bottom-up cost model. This modeling is further informed by 12 interviews conducted with new home builders, solar contractors, and other subject matter expert organizations. Our case study analysis generated three key considerations for other homebuilders including: 1. Educating local permitting, inspection, and in some cases utility officials on solar and storage products, designs, and code compliant building practices may be required. The need for education may decline as more local governments and utilities review and approve solar and storage projects. 2. Incorporating solar and storage systems into the homebuilding process can add complexity and related coordination challenges. This does not need to result in home construction delays, but can result in costly contractor "dry runs" to construction sites. 3. Deploying solar and storage at the time of new construction has significant economies of scale, which can improve the value proposition of the systems. The case study, extant literature, and interviews were used to model both existing and future solar and storage installation costs at time of new construction. Here, we find three key cost reduction opportunities relating to solar and battery storage hardware, customer acquisition, and overhead. If future contractors can maximize the cost reduction opportunities outlined here, residential new construction costs could decline by 8 - 25% by 2030, depending on the modeled scenario. Though we expect costs to decline through 2030, it is unclear which of these scenarios may ultimately appear. Interviewees further identified a variety of barriers across each cost category that could temper the savings shown here. At the same time, interviewees described several pathways to scale the new construction solar and storage market, beyond installation cost savings. Interviewees confirmed that changes in finance, rate design, resilience policies, deployment mandates, and DER aggregation could all support more market adoption than seen today. These findings suggest that there are significant opportunities to expand new construction markets and this research can serve as a baseline to assess progress in this segment through 2030.

14 SOLAR ENERGY↗

Markets and Economic Requirements for Fission Batteries and Other Nuclear Systems

Fission Batteries (FBs) are nuclear reactors defined by five characteristics which enable large-scale deployment: cost competitive, standardized sizes for economic mass production, easy installation and removal, secure and safe unattended operation with high reliability. FBs are not defined by technology or power level. Technical and market considerations suggest that most FBs will produce 20 to 30 MWt. This proceedings reports on the outcomes of two workshops that were held in January 2021 to better define markets and economic challenges for FBs. Three major markets were identified. The largest market is the industrial and commercial heat market. There are about 4000 industrial users (excluding utilities) that require more than one megawatt of heat. The number of customers versus size of heat demand was determined. In a low-carbon world there is the potential for many additional customers—including expanded biofuels production and district heat. The second market is for non-grid electricity. This includes co-generation plants that produce heat and electricity for a single customer. The third market is the maritime market with ~100,000 ships worldwide. In the United States, natural gas is the low-cost energy option today and will remain so unless constraints or taxes impact its use. If restrictions on greenhouse gas emissions, the FB competition includes natural gas with carbon capture, biofuels, hydrogen and grid electricity. Natural gas with carbon capture is not economically viable on a small scale. Biofuels may be expensive but may be the economically preferred option for locations with small energy demands of a few megawatts. Hydrogen is a potential competitor with many of the characteristics of natural gas. Grid electricity is not a competitive source of heat. For FBs to be economically competitive, the price of delivered heat must be $20-50/MWh ($6-15/million BTU). The economically competitive range for non-grid electricity is estimated at $70-100/MWh. These electricity prices are competitive with the retail prices of electricity in many parts of the United States for the customer. FBs are not expected to be competitive selling wholesale electricity to the grid. To achieve the aforementioned cost targets for heat and electricity markets, FB designers must (1) maximize the power output within the constraints of a FB (e.g., truck transportability, passive decay heat removal), (2) drastically reduce the size of onsite staff, (3) adopt core designs with low fuel costs (enrichment and fabrication), and (4) develop a system design that is efficiently manufactured in factories. The business case depends upon more than being just a replacement for natural gas. The largest incentives for adoption of FBs is where they create new markets and new sources of revenue. An example is the paper and pulp industry that burns biomass wastes to provide heat and electricity to make paper. An external heat source could meet the demand for heat and electricity by the paper process and enable converting waste biomass into liquid biofuels rather than burning to provide heat. Other markets, such as data centers, are driven by special energy requirements such as extreme reliability. Most customers are not in the energy business but need heat and electricity to produce a product—a manufactured good, education, retail sales (shopping malls), marine transport or some other product. As a consequence, there will be large incentives to lease rather than own FBs. Leasing avoids the regulatory challenges that remain with the owner of the FB. Leasing creates large incentives for FP standardization of sizes and transportability to maintain the value of the FB at the end of the lease—similar to the leasing of jet engines and aircraft. The economic constraints combined with technical constraints suggest competitive FBs will likely have outputs exceeding 10 MWt. There appear to be little incentives for very long-lived reactor cores because such machines require much larger inventories of fuel. Maintenance requirements and the options to provide technology updates may favor shorter lifetimes (~5 years). The assessment is that there is the potential for FBs to be economically viable and play a major role in global decarbonization in three markets: heat, non-grid electricity and maritime applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

How good are learning-based control v.s. model-based control for load shifting? Investigations on a single zone building energy system

Both model predictive control (MPC) and deep reinforcement learning control (DRL) have been presented as a way to approximate the true optimality of a dynamic programming problem, and these two have shown significant operational cost saving potentials for building energy systems. Furthermore, there is still a lack of in-depth quantitative studies on their approximation levels to the true optimality, especially in the building energy domain. To fill in the gap, this paper provides a numerical framework that enables the evaluation of the optimality levels of different controllers for building energy systems. This framework is then used to comprehensively compare the optimal control performance of both MPC and DRL controllers with given computation budgets for a single zone fan coil unit system. Note the optimality is estimated based on a user-specific selection of trade-off weights among energy costs, thermal comfort and control slew rates. Compared with the best optimality we can find through expensive optimization simulations, the best DRL agent can maximally approximate the optimality by 96.54%, which outperforms the best MPC whose optimality level is 90.11%. However, due to the stochasticity, the DRL agent is only expected to approximate the optimality by 90.42%, which is almost equivalent to the best MPC. Except for Proximal Policy Optimization (PPO), all DRL agents can have a better approximation to the optimality than the best MPC, and are expected to have better approximation than the MPC with a prediction horizon of 32 steps (15 min per step). In terms of reducing energy cost and thermal discomfort, MPC can outperform the rule-based control (RBC) by 18.47%–25.44%. DRL can be expected to outperform RBC by 18.95%–25.65% ,and the best DRL control policy can outperform RBC by 20.29%–29.72%. Although the comparison of the optimality level is performed in a perfect setting, e.g., MPC assumes perfect models, and DRL assumes a perfect offline training process and online deployment process, this can shed insight on their capabilities of approximating to the original dynamic programming problem.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Measurement of cross sections for mesonless charged-current muon neutrino interactions on argon with and without protons at MicroBooNE

urrent and upcoming neutrino experiments at Fermilab will rely on liquid argon time projection chambers (LArTPCs) as the primary detector technology. To reach the ambitious precision required for their physics goals, a detailed understanding of neutrino-argon scattering must be achieved. For the present Short-Baseline Neutrino program, the dominant reaction channel is charged-current muon neutrino interactions leading to mesonless final states with and without protons. Using a large data set of neutrino interactions recorded by the MicroBooNE LArTPC detector at Fermilab, we report progress towards new measurements of differential cross sections in this channel. The analysis leverages multiple event reconstruction paradigms and observables specifically chosen to maximize sensitivity to nuclear effects of interest for improving neutrino scattering models. Related previous cross-section results from MicroBooNE and a preview of what to expect from the new analysis will both be featured in this presentation.

Liu, Liang [Fermilab]↗

Perfecting one-loop BCJ numerators in SYM and supergravity

We take a major step towards computing D-dimensional one-loop amplitudes in general gauge theories, compatible with the principles of unitarity and the color-kinematics duality. For n-point amplitudes with either supersymmetry multiplets or generic non-supersymmetric matter in the loop, simple all-multiplicity expressions are obtained for the maximal cuts of kinematic numerators of n-gon diagrams. At n = 6, 7 points with maximal supersymmetry, we extend the cubic-diagram numerators to encode all contact terms, and thus solve the long-standing problem of simultaneously realizing the following properties: color-kinematics duality, manifest locality, optimal power counting of loop momenta, quadratic rather than linearized Feynman propagators, compatibility with double copy as well as all graph symmetries. Color-kinematics dual representations with similar properties are presented in the half-maximally supersymmetric case at n = 4, 5 points. The resulting gauge-theory integrands and their supergravity counterparts obtained from the double copy are checked to reproduce the expected ultraviolet divergences.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Optimal Sizing and Dispatch of Solar Power with Storage

Designers of utility-scale solar plants with storage, seeking to maximize some aspect of plant performance, face multiple challenges. In many geographic locations, there is significant penetration of photovoltaic generation, which depresses energy prices during the hours of solar availability. An energy storage system affords the opportunity to dispatch during higher-priced time periods, but complicates plant design and dispatch decisions. Solar resource variability compounds these challenges, because determining optimal system sizes requires simultaneously considering how the plant will be operated under the imposed market and weather conditions. We develop an approach to analyze the economic performance of hybrid and single-technology solar power plants, which incorporates optimal dispatch, and considers the expected electricity market and weather conditions. We utilize the System Advisor Model software package to simulate the operation of multiple renewable generation and energy storage technologies, in conjunction with hourly-fidelity generation decisions determined by a revenue-maximizing, mixed-integer linear program. We show that, under our assumed market and weather conditions, the lifetime benefit-to-cost ratio can be improved by 6 to 19 percent, relative to a baseline design without optimizing, and that a concentrating solar power with thermal energy storage design produces significantly more energy per year, but is less profitable under our cost assumptions.

black-box optimization↗

Cascading from $\mathscr{N}$ = 2 supersymmetric Yang–Mills theory to confinement and chiral symmetry breaking in adjoint QCD

We argue that adjoint QCD in 3 + 1 dimensions, with any SU(N) gauge group and two Weyl fermion flavors (i.e. one adjoint Dirac fermion), confines and spontaneously breaks its chiral symmetries via the condensation of a fermion bilinear. We flow to this theory from pure $\mathscr{N}$ = 2 SUSY Yang–Mills theory with the same gauge group, by giving a SUSY-breaking mass M to the scalars in the $\mathscr{N}$ = 2 vector multiplet. This flow can be analyzed rigorously at small M, where it leads to a deconfined vacuum at the origin of the $\mathscr{N}$ = 2 Coulomb branch. The analysis can be extended to all M using an Abelian dual description that arises from the N multi-monopole points of the $\mathscr{N}$ = 2 theory. At each such point, there are N −1 hypermultiplet Higgs fields h$^{i=1,2}_m$, which are SU(2) R doublets. We provide a detailed study of the phase diagram as a function of M, by analyzing the semi-classical phases of the dual using a combination of analytic and numerical techniques. The result is a cascade of first-order phase transitions, along which the Higgs fields h i m successively turn on, and which interpolates between the Coulomb branch at small M, where all h$^{i}_m$ = 0, and a maximal Higgs branch, where all h$^{i}_m$ ≠ 0, at sufficiently large M. We show that this maximal Higgs branch precisely matches the confining and chiral symmetry breaking phase of two-flavor adjoint QCD, including its broken and unbroken symmetries, its massless spectrum, and the expected large-N scaling of various observables. The spontaneous breaking pattern SU(2) R → U(1) R , consistent with the Vafa–Witten theorem, is ensured by an intricate alignment mechanism for the h$^{i}_m$ in the dual, and leads to a CP 1 sigma model of increasing radius along the cascade.

D’Hoker, Eric [Univ. of California, Los Angeles, C↗

GT Flex: A Coordinated Multi-Building Pilot Study

Buildings are a significant and untapped resource for providing utility electric grid services. Recent studies have estimated that buildings could reduce the peak demand on the electric grid in the U.S. by almost 25% through effective combinations of energy efficiency (EE) measures and load flexibility strategies (Langevin et al. 2021). The U.S. Department of Energy (DOE) has established a goal to triple energy efficiency and demand flexibility in both residential and commercial sections by 2030 compared to 2020 levels (Satchwell et al. 2021). Such findings place buildings alongside electric vehicles, photovoltaics, electric batteries, and other distributed energy resources (DERs) as primary technologies needed for supporting high renewable energy generation grids. Coordinating and optimizing multiple buildings and other DERs is more beneficial and valuable when compared with individual buildings and DERs operating as siloed resources, uncoordinated with others (Olgyay et al. 2020). A pilot study at the Georgia Institute of Technology (GIT) was conducted to evaluate value propositions of a multi-building scale project seeking carbon reduction, energy efficiency and grid-interactive capabilities, by demonstrating the means by which stakeholders can determine the technical and financial merits of grid-interactivity and energy efficiency technologies coordinated across multiple assets. The study focused on analyzing technical feasibility of deploying thermal load flexibility strategies at the multi-building scale, coordinated to not exceed existing infrastructure constraints at the pilot site. Results show that campus can provide 3-3.5 MW of potential load shed over a 4-hour event window through coordinated dispatch of thermal cooling load flexibility without exceeding existing infrastructure capacities. Under future high renewable scenarios, this thermal flexibility resource is also valuable when coordinated to reduce curtailment of intermittent renewables. Economic analyses were performed to effectively communicate various value propositions of grid-interactive and efficient building (GEB) thermal flexibility strategies. Load flexibility presents a financial value proposition to the campus today. By conducting rationalized, coordinated dispatch in response to real time price (RTP) fluctuations, the campus can benefit materially from daily price arbitrage. The RTP signal acts as an aggregating mechanism between the utility and customer to call on demand flexibility resources, with a large portion of the benefit deriving from a relatively small number of days. Realizing and maximizing this benefit with thermal load flexibility requires careful attention to the timing of pricing signals and parameterization of dispatch to overcome efficiency penalties. Grid value and signals are expected to evolve over time, and thermal load flexibility shows potential to adapt dispatch logic to support intermittent renewable generation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NBI optimization on SMART and implications for scenario development

Abstract The SMall Aspect Ratio Tokamak (SMART) under commissioning at the University of Seville, Spain, aims to explore confinement properties and possible advantages in confinement for compact/spherical tokamaks operating at negative vs. positive triangularity. This work explores the benefits of auxiliary heating through Neutral Beam Injection (NBI) for SMART scenarios beyond the initial Ohmic phase of operations, in support of the device’s mission. Expected values of electron and ion temperature achievable with NBI heating are first predicted for the current flat-top phase, including modeling to optimize the NBI injection geometry to maximize NBI absorption and minimize losses for a given equilibrium. Simulations are then extended for a selected case to cover the current ramp-up phase. Differences with results obtained for the flat-top phase indicate the importance of determining the plasma evolution over time, as well as self-consistently determining the edge plasma parameters for reliable time-dependent simulations. Initial simulation results indicate the advantage of auxiliary NBI heating to achieve nearly double values of pressure and stored energy compared to Ohmic discharges, thus significantly increasing the device’s performance. The scenarios developed in this work will also contribute to diagnostic development and optimization for SMART, as well as providing test cases for initial predictions of macro- and micro-instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Full forward model of galaxy clustering statistics with AbacusSummit light cones

ABSTRACT Novel summary statistics beyond the standard 2-point correlation function (2PCF) are necessary to capture the full astrophysical and cosmological information from the small-scale (r < 30h−1Mpc) galaxy clustering. However, the analysis of beyond-2PCF statistics on small scales is challenging because we lack the appropriate treatment of observational systematics for arbitrary summary statistics of the galaxy field. In this paper, we develop a full forward modelling pipeline for a wide range of summary statistics using the large high-fidelity AbacusSummit light cones that account for many systematic effects as well as remain flexible and computationally efficient to enable posterior sampling. We apply our forward model approach to a fully realistic mock galaxy catalog and demonstrate that we can recover unbiased constraints on the underlying galaxy–halo connection model using two separate summary statistics: the standard 2PCF and the novel k-th nearest neighbour (kNN) statistics, which are sensitive to correlation functions of all orders. We will demonstrate its strong constraining power on extended galaxy–halo connection models and cosmology in follow up papers. We expect this to become a powerful approach when applying to upcoming surveys such as DESI where we can leverage a multitude of summary statistics across a wide redshift range to maximally extract information from the non-linear scales.

79 ASTRONOMY AND ASTROPHYSICS↗

Challenges and Optimization of Mu2e Proton Target Design with Radiative Cooling

Mu2e, the Muon-to-Electron Conversion Experiment, aims to identify physics beyond the Standard Model, namely, the conversion of muons to electrons without the emission of neutrinos. The muons are produced from pions generated in a production target when it is hit by an 8 GeV proton beam from the Fermilab Booster/Main Injector. The proton target design space is strongly constrained by a one-year operating lifetime and the need for radiative cooling in a vacuum environment. Uncertainties in the lifetime of the existing baseline design – a monolithic, segmented tungsten target – are large, particularly due to unknown impacts of radiation damage at the very high proton fluences expected in the experiment. We have begun evaluation of a new design utilizing Inconel 718 over the WL10 used in the existing target design. As a result, the structural design of the target has evolved significantly. This evolution focuses on lowering the target temperature, minimizing obstruction to muons, increasing structural stability, maximizing fatigue lifetime, simplifying the fabrication process, and more. The thermal management, structural stability and fatigue lifetime are emphasized here. These optimizations have led to a promising new target design for the Mu2e experiment.

Liu, Z. [Fermilab]↗

Development of a cosmic ray oriented trigger for the fluorescence telescope on EUSO-SPB2

The Extreme Universe Space Observatory on a Super Pressure Balloon 2 (EUSO-SPB2), in preparation, aims to make the first observations of Ultra-High Energy Cosmic Rays (UHECRs) from near space using optical techniques. EUSO-SPB2 will prototype instrumentation for future satellite-based missions, including the Probe of Extreme Multi-Messenger Astrophysics (POEMMA) and K-EUSO. The payload will consist of two telescopes. The first is a Cherenkov telescope (CT) being developed to quantify the background for future below-the-limb very high energy (E 10 PeV) astrophysical neutrino observations, and the second is a fluorescence telescope (FT) being developed for detection of UHECRs. The FT will consist of a Schmidt telescope, and a 6192 pixel ultraviolet camera with an integration time of 1.05 s. The first step in the data acquisition process for the FT is a hardware level trigger in order to decide which data to record. In order to maximize the number of UHECR induced extensive air showers (EASs) which can be detected, a novel trigger algorithm has been developed based on the intricacies and limitations of the detector. Finally, the expected performance of the trigger has been characterized by simulations and, pending hardware verification, shows that EUSO-SPB2 is well positioned to attempt the first near-space observation of UHECRs via optical techniques.

79 ASTRONOMY AND ASTROPHYSICS↗