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DOE OSTI2017

Accurate Characterization of Real Networks from Inaccurate Measurements

Our nation's dependence on information networks makes it vital to anticipate disruptions or find weaknesses in these networks. But networks like the Internet are vast, distributed, and there is no mechanism to completely collect their structure. We are restricted to specific data collection schemes (like traceroute samples from router interfaces) that examine tiny portions of such a network. It has been empirically documented and theoretically proven that these measurements have significant biases, and direct inferences from them will be wrong. But these data collection mechanisms have limited flexibility and cannot be easily modified. Moreover, in many applications there are limits on how much data can be collected. How do we make accurate inferences of network properties with biased and limited measurements? The general problem this report deals with is how to work with incompletely observed networks. We will present several different approaches to this problem. First we will present an approach to estimate the degree distribution of a graph by sampling only a small portion of the vertices. This algorithm provides provably accurate results with sublinear samples. An alternative approach would be to try to enhance the information in the by selective collecting new information by probing for neighbors of a vertex or presence of individual edges. A different setting for working with incomplete arises when we have full access to local information, but do not have any global version of the graph. Can we still identify critical nodes in such a graph? We present an approach to identify such nodes efficiently. Finally, how can we put these ideas together to identify the structure of a network? We present an approach that can complement the existing approaches for network mapping. We start with an estimate of network structure based on existing network mapping methods. Then we find a critical router in the network, use the traffic through this network to selectively collect new data to enhance our prediction.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Transition between protein-like and polymer-like dynamic behavior: Internal friction in unfolded apomyoglobin depends on denaturing conditions

Equilibrium dynamics of different folding intermediates and denatured states is strongly connected to the exploration of the conformational space on the nanosecond time scale and might have implications in understanding protein folding. For the first time, the same protein system apomyoglobin has been investigated using neutron spin-echo spectroscopy in different states: native-like, partially folded (molten globule) and completely unfolded, following two different unfolding paths: using acid or guanidinium chloride (GdmCl). While the internal dynamics of the native-like state can be understood using normal mode analysis based on high resolution structural information of myoglobin, for the unfolded and even for the molten globule states, models from polymer science are employed. The Zimm model accurately describes the slowly-relaxing, expanded GdmCl-denaturated state, ignoring the individuality of the different aminoacid side chain. The dynamics of the acid unfolded and molten globule state are similar in the framework of the Zimm model with internal friction, where the chains still interact and hinder each other: the first Zimm relaxation time is as large as the internal friction time. Transient formation of secondary structure elements in the acid unfolded and presence of α-helices in the molten globule state lead to internal friction to a similar extent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Cryo-electron tomography related radiation-damage parameters for individual-molecule 3D structure determination

To understand the dynamic structure–function relationship of soft- and biomolecules, the determination of the three-dimensional (3D) structure of each individual molecule (nonaveraged structure) in its native state is sought-after. Cryo-electron tomography (cryo-ET) is a unique tool for imaging an individual object from a series of tilted views. However, due to radiation damage from the incident electron beam, the tolerable electron dose limits image contrast and the signal-to-noise ratio (SNR) of the data, preventing the 3D structure determination of individual molecules, especially at high-resolution. Although recently developed technologies and techniques, such as the direct electron detector, phase plate, and computational algorithms, can partially improve image contrast/SNR at the same electron dose, the high-resolution structure, such as tertiary structure of individual molecules, has not yet been resolved. Here, we review the cryo-electron microscopy (cryo-EM) and cryo-ET experimental parameters to discuss how these parameters affect the extent of radiation damage. This discussion can guide us in optimizing the experimental strategy to increase the imaging dose or improve image SNR without increasing the radiation damage. With a higher dose, a higher image contrast/SNR can be achieved, which is crucial for individual-molecule 3D structure. With 3D structures determined from an ensemble of individual molecules in different conformations, the molecular mechanism through their biochemical reactions, such as self-folding or synthesis, can be elucidated in a straightforward manner.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

A Principled Framework to Assess the Information-Theoretic Fitness of Brain Functional Sub-Circuits

In systems and network neuroscience, many common practices in brain connectomic analysis are often not properly scrutinized. One such practice is mapping a predetermined set of sub-circuits, like functional networks (FNs), onto subjects’ functional connectomes (FCs) without adequately assessing the information-theoretic appropriateness of the partition. Another practice that goes unchallenged is thresholding weighted FCs to remove spurious connections without justifying the chosen threshold. This paper leverages recent theoretical advances in Stochastic Block Models (SBMs) to formally define and quantify the information-theoretic fitness (e.g., prominence) of a predetermined set of FNs when mapped to individual FCs under different fMRI task conditions. Our framework allows for evaluating any combination of FC granularity, FN partition, and thresholding strategy, thereby optimizing these choices to preserve the important topological features of the human brain connectomes. By applying to the Human Connectome Project with Schaefer parcellations at multiple levels of granularity, the framework showed that the common thresholding value of 0.25 was indeed information-theoretically valid for group-average FCs, despite its previous lack of justification. Our results pave the way for the proper use of FNs and thresholding methods, and provide insights for future research in individualized parcellations.

Duong-Tran, Duy (ORCID:0009000944967575)↗

NASA NTRS2018

Characterizing Material Scalability for Ultralight Lattice Design

Stiff yet ultra-light lattice structures constructed using digital materials have many practical applications as the building block for aircraft and other structures. By furthering our understanding of how material configuration affects the structural properties of an ultralight lattice, we can intelligently design these structures based on their intended function. Here we compare the behavior of ultralight lattice structures when fabricated by different materials. The individual unit cells of the lattice structures are referred to as voxels. The stiffness, elastic modulus, and yield strength of the specimens in compression and tension are determined through mechanical testing. Specimens are tested both as single voxel as well as 4x4x4 voxel constructions on an Instron 5982 Universal Testing System until failure. Each voxel is manufactured in bulk through injection molding, with a unit cell pitch of 76.2 mm. Individual voxels are fastened with machine screws and nuts to create assemblies. Four separate materials are used as voxel compositions in this experiment. These include a homogeneous polymer referred to as Ultem 1000, a glass-fiber reinforced polymer referred to as Ultem 2200, a polymer with chopped carbon fibers as 30% of its fill, and homogenous polypropylene. This work compares mechanical behavior, as well as the convergence behavior of the lattice as the size of the lattice assembly increases for various materials. The goal of this study is to characterize the behavior of homogenous lattices such that heterogenous lattices can be designed with different material voxels to achieve target material properties for ultralight space applications.

Sajjadi, Afsheen↗

DOE OSTI2022

Interface effect of Fe and Fe 2 O 3 on the distributions of ion induced defects

The stability of structural materials in extreme nuclear reactor environments—with high temperature, high radiation, and corrosive media—directly affects the lifespan of the reactor. In such extreme environments, an oxide layer on the metal surface acts as a passive layer protecting the metal underneath from corrosion. To predict the irradiation effect on the metal layer in these metal/oxide bilayers, nondestructive depth-resolved positron annihilation lifetime spectroscopy (PALS) and complementary transmission electron microscopy (TEM) were used to investigate small-scale defects created by ion irradiation in an epitaxially grown (100) Fe film capped with a 50 nm Fe 2 O 3 oxide layer. In this study, the evolution of induced vacancies was monitored, from individual vacancy formation at low doses—10 –5 dpa—to larger vacancy cluster formation at increasing doses, showing the sensitivity of positron annihilation spectroscopy technique. Furthermore, PALS measurements reveal how the presence of a metal–oxide interface modifies the distribution of point defects induced by irradiation. TEM measurements show that irradiation induced dislocations at the interface is the mechanism behind the redistribution of point defects causing their accumulation close to the interface. Finally, this work demonstrates that the passive oxide layers formed during corrosion impact the distribution and accumulation of radiation induced defects in the metal underneath and emphasizes that the synergistic impact of radiation and corrosion will differ from their individual impacts.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Partial connectomes of labeled dopaminergic circuits reveal non-synaptic communication and axonal remodeling after exposure to cocaine

Dopaminergic (DA) neurons exert profound influences on behavior including addiction. However, how DA axons communicate with target neurons and how those communications change with drug exposure remains poorly understood. We leverage cell type-specific labeling with large volume serial electron microscopy to detail DA connections in the nucleus accumbens (NAc) of the mouse (Mus musculus) before and after exposure to cocaine. We find that individual DA axons contain different varicosity types based on their vesicle contents. Spatially ordering along individual axons further suggests that varicosity types are non-randomly organized. DA axon varicosities rarely make specific synapses (<2%, 6/410), but instead are more likely to form spinule-like structures (15%, 61/410) with neighboring neurons. Days after a brief exposure to cocaine, DA axons were extensively branched relative to controls, formed blind-ended ‘bulbs’ filled with mitochondria, and were surrounded by elaborated glia. Finally, mitochondrial lengths increased by ~2.2 times relative to control only in DA axons and NAc spiny dendrites after cocaine exposure. We conclude that DA axonal transmission is unlikely to be mediated via classical synapses in the NAc and that the major locus of anatomical plasticity of DA circuits after exposure to cocaine are large-scale axonal re-arrangements with correlated changes in mitochondria.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1994

Evolution of radio galaxies to z = 1

We report Very Large Array (VLA) A-configuration studies of a sample of 49 radio galaxies at redshift less than 1. These were selected with no prior knowledge of their morphology and were chosen to match the redshift and luminosity distribution of a previously studied sample of radio-loud quasars. We compare the radio galaxies with the quasar sample and also with a sample of 29 radio galaxies selected for steep spectrum and double-lobe structure. We find that the radio galaxies have more luminous lobes and mostly weaker cores, and there is no population of one-sided sources associated with the galaxies. The radio galaxies' lobe length ratios and lobe power ratios differ from quasars. The overall sizes of the two types of sources are similar, but the radio galaxies have a 3 times larger upper envelope. The distribution of bend angles is similar but the radio galaxies have fewer very bent and straight sources. We discuss these and other comparisons in detail and suggest that while quasars appear to be viewed within a cone and radio galaxies outside it, the two types of source also have intrinsic differences, and both have individual growth and evolution scenarios. This is supported by previously observed differences in optical properties between the two source types.

Hutchings, J. B.↗

DOE OSTI2014

Predicting error in detecting mammographic masses among radiology trainees using statistical models based on BI-RADS features

Purpose: The purpose of this study is to explore Breast Imaging-Reporting and Data System (BI-RADS) features as predictors of individual errors made by trainees when detecting masses in mammograms. Methods: Ten radiology trainees and three expert breast imagers reviewed 100 mammograms comprised of bilateral medial lateral oblique and craniocaudal views on a research workstation. The cases consisted of normal and biopsy proven benign and malignant masses. For cases with actionable abnormalities, the experts recorded breast (density and axillary lymph nodes) and mass (shape, margin, and density) features according to the BI-RADS lexicon, as well as the abnormality location (depth and clock face). For each trainee, a user-specific multivariate model was constructed to predict the trainee's likelihood of error based on BI-RADS features. The performance of the models was assessed using area under the receive operating characteristic curves (AUC). Results: Despite the variability in errors between different trainees, the individual models were able to predict the likelihood of error for the trainees with a mean AUC of 0.611 (range: 0.502–0.739, 95% Confidence Interval: 0.543–0.680,p < 0.002). Conclusions: Patterns in detection errors for mammographic masses made by radiology trainees can be modeled using BI-RADS features. These findings may have potential implications for the development of future educational materials that are personalized to individual trainees.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2019

Diffusion Behavior of Differently Charged Molecules in Self-Assembled Organic Nanotubes Studied Using Imaging Fluorescence Correlation Spectroscopy

The diffusion behavior of fluorescent molecules within bolaamphiphile-based organic nanotubes (ONTs) was systematically explored using imaging fluorescence correlation spectroscopy (imaging FCS). Anionic sulforhodamine B (SRB), zwitterionic/cationic rhodamine B (RB) or cationic rhodamine 123 (R123) was loaded into ONTs having cylindrical hollow structures (ca. 10 nm in inner diameter) with amine and glucose groups on the inner and outer surfaces, respectively. Wide-field fluorescence video microscopy was used to acquire imaging FCS data for dye-doped ONTs in aqueous solutions of different ionic strengths (1 – 500 mM) at different pH (3.4 – 8.4). The diffusion behavior of these dyes was discussed on the basis of their apparent diffusion coefficients (D) that were determined by autocorrelating the time transient of fluorescence intensity at each pixel on an ONT. Molecular diffusion in the ONTs was significantly slowed by molecule-nanotube interactions, as shown by the very small D (10-1 – 10-2 µm2/s). The pH-dependence of D revealed that dye diffusion was basically controlled by electrostatic interactions associated with the protonation of the amine groups on the ONT inner surface. The pH-dependent change in D was observed over a wide pH range, possibly due to electrostatically induced variations in the pKa of the densely packed ammonium ions on the ONT inner surface. On the other hand, the influence of ionic strength on D was relatively unclear, suggesting the involvement of non-coulombic interactions with the ONTs in molecular diffusion. Notably, individual ONTs of different lengths (1 – 5 µm) afforded similar diffusion coefficients for each type of dye at each solution condition, implying that the properties of ONTs were uniform in terms of solute loading and release. These conclusions highlight the characteristics of molecular diffusion behavior within the ONTs, and will help in the design of organic nanotubes better suited for use as drug vehicles and contaminant adsorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

SU-D-18A-06: Variation of Controlled Breath Hold From CT Simulation to Treatment and Its Dosimetric Impact for Left-Sided Breast Radiotherapy with a Real-Time Optical Tracking System

Purpose: Different breath-hold (BH) maneuvers (abdominal breathing vs. chest breathing) during CT simulation and treatment can lead to chest wall positional variation. The purpose of this study is to quantify the variation of active breathing control (ABC)-assisted BH and estimate its dosimetric impact for left-sided whole-breast radiotherapy with a real-time optical tracking system (OTS). Methods: Seven breast cancer patients were included. An in-house OTS tracked an infrared (IR) marker affixed over the xiphoid process of the patient at CT simulation and throughout the treatment course to measure BH variations. Correlation between the IR marker and the breast was studied for dosimetric purposes. The positional variations of 860 BHs were retrospectively incorporated into treatment plans to assess their dosimetric impact on breast and cardiac organs (heart and left anterior descending artery [LAD]). Results: The mean intrafraction variations were 2.8 mm, 2.7 mm, and 1.6 mm in the anteroposterior (AP), craniocaudal (CC), and mediolateral (ML) directions, respectively. Mean stability in any direction was within 1.5 mm. A general trend of BH undershoot at treatment relative to CT simulation was observed with an average of 4.4 mm, 3.6 mm, and 0.1 mm in the AP, CC, and ML directions, respectively. Undershoot up to 12.6 mm was observed for individual patients. The difference between the planned and delivered dose to breast targets was negligible. The average planned/delivered mean heart doses, mean LAD doses, and max LAD doses were 1.4/2.1, 7.4/15.7, and 18.6/31.0 Gy, respectively. Conclusion: Systematic undershoot was observed in ABC-assisted BHs from CT simulation to treatment. Its dosimetric impact on breast coverage was minimized with image guidance, but the benefits of cardiac organ sparing were degraded. A real-time tracking system can be used in junction with the ABC device to improve BH reproducibility.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Interactive effects of salinity, redox, and colloids on greenhouse gas production and carbon mobility in coastal wetland soils

Coastal wetlands, including freshwater systems near large lakes, rapidly bury carbon, but less is known about how they transport carbon either to marine and lake environments or to the atmosphere as greenhouse gases (GHGs) such as carbon dioxide and methane. This study examines how GHG production and organic matter (OM) mobility in coastal wetland soils vary with the availability of oxygen and other terminal electron acceptors. We also evaluated how OM and redox-sensitive species varied across different size fractions: particulates (0.45–1μm), fine colloids (0.1–0.45μm), and nano particulates plus truly soluble (<0.1μm; NP+S) during 21-day aerobic and anaerobic slurry incubations. Soils were collected from the center of a freshwater coastal wetland (FW-C) in Lake Erie, the upland-wetland edge of the same wetland (FW-E), and the center of a saline coastal wetland (SW-C) in the Pacific Northwest, USA. Anaerobic methane production for FW-E soils were 47 and 27,537 times greater than FW-C and SW-C soils, respectively. High Fe 2+ and dissolved sulfate concentrations in FW-C and SW-C soils suggest that iron and/or sulfate reduction inhibited methanogenesis. Aerobic CO 2 production was highest for both freshwater soils, which had a higher proportion of OM in the NP+S fraction (64±28% and 70±10% for FW-C and FW-E, respectively) and organic C:N ratios reflective of microbial detritus (5.3±5.3 and 5.3±7.0 for FW-E and FW-C, respectively) compared to SW-C, which had a higher fraction of particulate (58±9%) and fine colloidal (19±7%) OM and organic C:N ratios reflective of vegetation detritus (11.4 ± 1.7). The variability in GHG production and shifts in OM size fractionation and composition observed across freshwater and saline soils collected within individual and across different sites reinforce the high spatial variability in the processes controlling OM stability, mobility, and bioavailability in coastal wetland soils.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Whole‐lake invasive crayfish removal and qualitative modeling reveal habitat‐specific food web topology

Abstract Patterning of the presence/absence of food web linkages (hereafter topology) is a fundamental characteristic of ecosystems that can influence species responses to perturbations. However, the insight from food web topology into dynamic effects of perturbations on species is potentially hindered because most described topologies represent data integrated across spatial and temporal scales. We conducted a 10‐year, whole‐lake experiment in which we removed invasive rusty crayfish ( Orconectes rusticus ) from a 64‐ha north‐temperate lake and monitored responses of multiple trophic levels. We compared species responses observed in two sub‐habitats to the responses predicted from all topologies of an integrated, literature‐informed base food web model of 32 potential links. Out of 4.3 billion possible topologies, only 308,833 (0.0072%) predicted responses that qualitatively matched observed species responses in cobble habitat, and only 12,673 (0.0003%) matched observed responses in sand habitat. Furthermore, when constrained to predictions that both matched observed responses and were highly reliable (i.e., predictions were robust to link strength values), only 5040 (0.0001%) and 140 (0.000003%) topologies were identified for cobble and sand habitats, respectively. A small number of linkages were nearly always present in these valid, reliable networks in sand, while a greater variety of possible network configurations were possible in cobble. Direct links involving invasive rusty crayfish were more important in cobble, while indirect effects involving Lepomis spp. were more important in sand. Importantly, the importance of individual species linkages differed dramatically among cobble and sand sub‐habitats within a single lake, even though species composition was identical. Although the true topology of food webs is difficult to determine, constraining topologies to include spatial resolution that matches observed experimental outcomes may reduce possibilities to a small number of plausible alternatives.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Supersymmetric Landau-Ginzburg tensor models

We study two dimensional N = (2, 2) Landau-Ginzburg models with tensor valued superfields with the aim of constructing large central charge superconformal field theories which are solvable using large N techniques. We demonstrate the viability of such constructions and motivate the study of anisotropic tensor models. Such theories are a novel deformation of tensor models where we break the continuous symmetries while preserving the large N solvability. Specifically, we examine theories with superpotentials involving tensor contractions chosen to pick out melonic diagrams. The anisotropy is introduced by further biasing individual terms by different coefficients, all of the same order, to retain large N scaling. We carry out a detailed analysis of the resulting low energy fixed point and comment on potential applications to holography. Along the way we also examine gauged versions of the models (with partial anisotropy) and find generically that such theories have a non-compact Higgs branch of vacua.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2015

Non-stationary Return Levels of CMIP5 Multi-model Temperature Extremes

The objective of this study is to evaluate to what extent the CMIP5 climate model simulations of the climate of the twentieth century can represent observed warm monthly temperature extremes under a changing environment. The biases and spatial patterns of 2-, 10-, 25-, 50- and 100-year return levels of the annual maxima of monthly mean temperature (hereafter, annual temperature maxima) from CMIP5 simulations are compared with those of Climatic Research Unit (CRU) observational data considered under a non-stationary assumption. The results show that CMIP5 climate models collectively underestimate the mean annual maxima over arid and semi-arid regions that are most subject to severe heat waves and droughts. Furthermore, the results indicate that most climate models tend to underestimate the historical annual temperature maxima over the United States and Greenland, while generally disagreeing in their simulations over cold regions. Return level analysis shows that with respect to the spatial patterns of the annual temperature maxima, there are good agreements between the CRU observations and most CMIP5 simulations. However, the magnitudes of the simulated annual temperature maxima differ substantially across individual models. Discrepancies are generally larger over higher latitudes and cold regions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Study of slip activity in a Mg-Y alloy by in situ high energy X-ray diffraction microscopy and elastic viscoplastic self-consistent modeling

Slip activity from various slip modes largely determines the yield strength and ductility of Mg alloys. Solid solution elements in Mg can change the slip activity dramatically. In this paper, far-field high energy X-ray diffraction microscopy (FF-HEDM) is employed to study slip activity in a Mg-3wt%Y alloy during an in situ tensile experiment. The specimen was incrementally loaded up to 3% engineering strain along the rolling direction. At each load step, FF-HEDM data were collected to track the crystallographic orientation, center of mass, and stress tensor changes of nearly 1000 grains in the probed volume. By analyzing the change in orientation and stress tensor of individual grains at different load steps, it is possible to identify the activated slip systems and measure their critical resolved shear stress (CRSS) values. Prismatic slip and pyramidal I slip are found to be very active in this alloy. The estimated CRSS values for basal slip, prismatic slip and pyramidal I slip are 12 MPa, 38 MPa, and 36 MPa, respectively. These CRSS values were applied in a dislocation-based elastic viscoplastic self-consistent (EVPSC) model that successfully simulated the tensile stress-strain curve from the FF-HEDM experiment. The model also qualitatively predicted the crystal rotation in most of the selected grains, though it underestimated the internal stress and the magnitude of crystal rotation in these grains. Influence of solute Y on the strength and ductility of Mg alloys is discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Assessing parallel path cooling tower performance via artificial neural networks

Real-time monitoring of a research nuclear reactor, a system in which all generated power is dissipated to the environment, can be performed via analysis of the heat rejection from the cooling system. Given an inlet water temperature and flow rate, the reactor power can be well-approximated from the outlet water temperature; however, the instrumentation to measure outlet conditions may not be robust or accurate. If we know how a cooling tower performs from historical data, but cannot measure the outlet temperature, a mathematical representation of the system can be inverted to obtain the outlet water temperature that describes the cooling capacity. Unfortunately, model inversion processes are computationally expensive. To address this, an artificial neural network (ANN) is implemented to assess the performance of a multi-cell cooling tower for a nuclear reactor. This approach leverages the Merkel model to obtain an extensive data set describing performance of the cooling tower cells throughout a wide array of potential operating conditions. The Merkel model is expressed as a function of four parameters: the inlet and outlet water temperatures, inlet air wet bulb temperature, and ratio of liquid-to-gas mass flow rates (L/G), which together provide a non-dimensional number indicative of cooling tower performance, called the Merkel integral. Computing a 4-dimensional data structure that describes finite combinations of the Merkel integral, an inverse model is then generated using an ANN to determine the cell outlet water temperature from the other three model parameters along with the computed Merkel integral. Compared to traditional model inversion methods, the ANN reduces the computational time by approximately 4 orders of magnitude, with effectively no sacrifice to solution accuracy, and could be applied for different cooling towers in the event the performance curve is known. Finally, three use cases of the ANN are then reviewed: (1) determining the cell outlet water temperatures when gas flow at rated conditions (GFRC) is known, (2) performing the prior case without knowledge of the GRFC, and (3) assessing performance differences between the individual tower cells.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Design and dispatch optimization of packaged ice storage systems within a connected community

The traditional implementation of cool thermal energy storage (CTES) must be reimagined within the context of a dynamic grid and smart buildings operating as connected communities. As most buildings do not operate central chillers or connect to district cooling loops, this necessitates a broader use of packaged CTES. Our objective is to begin answering the question of how such packaged CTES should be implemented within a connected community. We do so by presenting a simulation–optimization workflow employing building energy modeling software and a mixed-integer linear program to design and dispatch a packaged CTES technology to achieve minimum total annual cost. We demonstrate this methodology on a seven-building case study using current utility rates and find that total annual cooling energy costs can be reduced by 17.8% compared to baseline, after accounting for the cost of storage. We perform three parametric sensitivity studies to evaluate modeling assumptions and obtain the prioritization of storage procurement as a function of annualized life-cycle cost of storage. We find that a community optimization approach provides significantly different results than individual building optimizations and provides greater savings compared to baseline.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗