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This is a collection of papers drawn from the 2019 ASME InterPACK Conference. The content spans the areas of heterogeneous integration, servers, flexible and wearable electronics, photonics, power electronics, energy storage, and autonomous and electric vehicles.
To meet 2050 decarbonization targets, widespread building electrification is a critical complement to clean power generation. Behind-the-meter storage (BTMS) (e.g., battery electric energy storage [EES] and thermal energy storage [TES]) integrated with buildings or building end uses to store and supply energy at optimal times can minimize burdens associated with operation, planning, and upgrades to the electrical grid sometimes triggered by building electrification. Such BTMS systems can serve the dual purpose of providing enhanced resilience at the building and grid level, and support the deployment of renewable generation needed for wide-scale decarbonization. While TES can cost-effectively shed and shift thermal loads, it cannot generally backup or shift non-thermal building end uses. EES, by contrast, is more expensive, but applicable to all end uses (i.e., thermal and electrical loads). Combined together, these storage systems can be traded off against one another to perform optimally in meeting demand flexibility, decarbonization goals, and energy resilience of the buildings at a lower total system cost. This paper proposes a framework to define BTMS benefits, provides four illustrative electrification scenarios using TES and EES, and discusses the combined TES/EES benefits with building energy modeling results. The paper also highlights potential barriers to adoption of BTMS and a path forward.
The STAT7 software was developed to perform steady-state, single-phase thermal hydraulics analysis of plate-fueled reactors based on statistical propagation of uncertainties. Application of the software includes non-power research and test reactor analysis, and it has been used for the conversion to low- enriched uranium fuel of U.S. High Performance Research Reactors such as the Massachusetts Institute of Technology Research Reactor. Since it can be necessary to repeat reactor safety analysis, such as during fuel reloading, STAT7 accommodates flexibility in analyzing many practical aspects of reactor fuel management. STAT7 uses a Monte Carlo approach to model uncertainty in common fuel fabrication parameters and other key reactor operating parameters required for reactor thermal hydraulics analysis. These safety calculations are ultimately intended to protect against high fuel plate temperatures due to critical heat flux, or onset of flow instability. STAT7 supports water properties based on the IAPWS-IF97 functions (The International Association for the Properties of Water and Steam Industrial Formulation 1997 for the Thermodynamic Properties of Water and Steam) in addition to fitted functions. STAT7 predicts axial profiles of fuel, cladding, and coolant temperature along a lateral stripe that runs the full length of the fuel plate from the bottom to the top. STAT7 can simultaneously analyze every axial node in each lateral stripe of all fuel plates and coolant channels in every fuel element of an entire reactor core. Power splits are calculated for each axial node of each plate to determine how much of the power goes out each face of the plate. In a single execution, STAT7 can be used to perform full core analysis by analyzing the margin to onset of nucleate boiling and onset of flow instability for each axial node of each stripe of each plate of each fuel element in the core.
Advanced reactors often involve complicated thermal-fluid (T-F) phenomena. Modeling such phenomena with the traditional one-dimensional (1-D) system code is a challenging task. The System Analysis Module (SAM), a modern nuclear system code, has developed a coarse mesh multi-dimensional (multi-D) flow model to capture the spatial effect of T-F phenomena in advanced reactors. As a coarse mesh solver, constitutive relations are required for SAM's multi-D model for unresolved fine-scale physics, such as turbulence. Here this work presents a novel approach that integrates neural networks as data-driven closure for SAM's multi-D flow model. The data-driven closure is trained with fine-resolution data to ensure its accuracy while maintaining a coarse mesh setup to ensure its efficiency and consistency with SAM. We demonstrate the applicability of this SAM-ML capability in an open volume thermal stratification problem, where a neural network model serves as the eddy viscosity closure. A customized interface between the neural network and SAM is developed to ensure flexible and efficient data exchange. The SAM-ML results demonstrate superior performance compared to SAM's built-in zero-equation eddy viscosity closure. The case study shows that although the generalization capability of the data-driven closure still needs to be improved for different transient case or different geometric setup, SAM -ML demonstrates good potential for challenging simulation problems with improved accuracy and computational efficiency.
Commercial oxygen generation technologies deploy either cryogenic air separation or vacuum pressure swing adsorption (VPSA). These technologies can provide nearly pure oxygen but are only economically viable at oxygen production rates of 100-7,000 tonnes/day. The state-of-theart cryogenic air separation plants are impending the theoretical limits of thermodynamic efficiency but cannot be scaled down to cater future needs. Therefore, there is great incentive to develop a new approach for oxygen separation that can accommodate the upcoming demands. Our proposed research approach address to find novel methodologies to provide energy efficient modular O 2 on demand systems for modular gasification and other applications. Small scale modular systems for O 2 production offer certain benefits including enhanced energy efficiency, reduced operating costs and flexibility to tailor location specific needs. Our hypothesis is that a small modular system could be engineered using solvent-based capture and thermal release of oxygen, to enable “oxygen on demand” for any combustion-related technology.
U.S. industry sectors used 26.2 quadrillion Btu and accounted for 33% of total energy consumption in 2021 according to the Energy Information Agency. Industrial process heat accounts for 70% of industrial energy use with application temperatures ranging from 60 degrees -1100 degrees C. Industry processes, heavily relying on fossil fuels of cheap coal or natural gas, differ widely in operating conditions and load requirements which makes them difficult to standardize and imposes great challenges in decarbonization. Industry processes require reliable energy supply and vary widely in temperature ranges. Storing energy from renewable sources is necessary to improve reliability and to mitigate renewable intermittency when replacing carbon fuel-based heat supplies to achieve energy savings and reduce emissions. To this end, we have developed a particle-based thermal energy storage (TES) technology using low-cost and highly stable silica sand as a storage medium. The economic and performance-based analysis is key for renewable energy sources to reliably supply industry process heat and ultimately displace fossil fuels for decarbonization. The diversified industrial processes need case-by-case analysis and design. Therefore, an adaptive modeling tool is key for renewable power with energy storage to meet industry demands. Thus, a modeling tool to simulate a solar industry process heat system using the particle TES has been developed using the object-oriented equation-based language Modelica and the commercial platform of Modelon Impact. The Modelica-based software tool provides a general simulation environment for the design of reliable solar energy sources integrated with TES for various industrial process applications at different temperatures for economic competence with fossil fuels such as coal and natural gases. It uses both customized and standard component modeling modules in Modelon libraries for the flexibility to be adapted to a specific energy demand application. The particle TES system establishes a uniform energy supply platform with an efficient heat exchanger and particle thermal energy reservoir integrated with renewable powers. The particle TES system can provide a wide temperature range and can have a large storage temperature difference that increases storage energy density; therefore, it can be an adaptable energy storage system integrated with renewable power to supply 24/7 heat for industry decarbonization.
Cellulose, often considered a highly promising substitute for petroleum-based plastics, offers several compelling advantages, including abundant availability, cost-effectiveness, environmental friendliness, and biodegradability. However, its inherent highly crystalline structure and extensive hydrogen-bonded network pose challenges for processing and recycling. Here, in this study, we introduce the concept of cellulose vitrimers (CVs), wherein dynamic bonds are incorporated to reconfigure the hydrogen-bonded network, resulting in a mechanically robust, highly transparent material. CVs exhibit exceptional malleability, thermal stability, and noteworthy resistance to water and solvents. Due to the dynamic bond disassociation, CVs can be effectively chemically recycled using a well-established “dissolution-and-reforming” process. Moreover, CVs have proven successful as flexible substrate materials for organic solar cells, outperforming traditional petroleum-based polyethylene naphthalate (PEN). Given these advantages, CVs have the potential to replace conventional petroleum-based materials as recyclable and environmentally friendly alternatives, particularly within the realm of electronic devices and displays.
Zirconium Hydride (ZrH x ) is a moderator material for TRIGA reactors and SNAP-10A.The thermal scattering has the behavior of quantum oscillator favorable for moderator feedback. ZrH x occurs as a corrosion product in LWR. Previously new phase specific TSL evaluations were generated and submitted to ENDF/B- VIII.1. These include the effects of crystal structure on elastic scattering of Zr(ZrH x ), permit flexibility in stoichiometry for use in reactor physics calculations and fuel characterization, and expand the TSL material sub-library. ENDF/B-VIII.0 ZrH TSLs do not distinguish between material phase. Current work involves preliminary validation & verification testing on the effect of TSLs on critical mass and associated thermal flux.
Additive manufacturing, or simply 3D printing (3DP), where objects are built through layer-wise material deposition, has gained significant academic and industrial attention as a result of the development of advanced and functional materials requiring rapid, customized, and flexible solutions. In the context of green manufacturing, diversifying environmentally and economically sustainable material portfolios is an essential endeavor for the success of 3DP technology that uses widely available, highly valuable, and renewable materials. Here, we used stereolithography (SLA) for processing methacrylate-based photocurable resins containing crab shell-derived chitin nanowhiskers (CNWs), which are surface-functionalized by reactive acrylate groups. Results from full spectral, thermal, structural, and topological analyses corroborate not only the surface functionalization of CNWs but also indicate the presence of these photocurable CNW (pCNW) fillers in the 3D-printed nanocomposites. Owing to the strong interfacial bond induced by the physical and chemical crosslinking between the pCNW and methacrylate (MA) polymer matrix, the internally formulated nanocomposites displayed enhanced thermomechanical properties (e.g., storage modulus and glass transition temperature) compared to those of commercially available pure SLA resins. For instance, the inclusion of 0.5 wt % pCNW improved the tensile strength and stiffness to up to 78 and 71%, respectively, without compromising the toughness and ductility of the printed material. Accordingly, this result also evidences the compatibility between the filler and resin materials. Consequently, the formation of a crosslinked network in the nanocomposite structure results in a higher thermal stability and activation energy (i.e., up to ~79%) for all the hybrid materials than the pristine MA. Finally, the high-resolution SLA print features, dimensional accuracy, and enhanced mechanical performance of our microstructure-forming functionalized chitin-based nanocomposites make them promising materials for a wide range of robust and high-performance industrial applications.
Collagen-mimetic peptides (CMPs) are engineered molecules designed to replicate the triple-helical structure of natural collagen. A repeating x–y-Gly sequence is the defining motif of CMPs and is critical to their triple-helical structure and stability. Substitutions to the residues occupying the x and y positions present a means to modulate the CMP structure and properties. Peptoid residues—N-substituted glycine derivatives—present an attractive potential substitution due to their thermal stability, proteolytic resistance, biocompatibility, and diverse palette of non-natural side chains, but also tend to introduce a high degree of backbone flexibility that can diminish the stability of the triple helix. In this work, we report a computational active learning cycle comprising molecular dynamics simulation, Gaussian process regression, and Bayesian optimization to computationally identify a number of promising peptoid substitutions predicted to stabilize the desired quaternary structure through side chain interactions and produce stable peptoid-based collagen-like triple helices. To experimentally test the computational predictions, a top candidate identified by the screen was synthesized and imaged using scanning electron microscopy to resolve fibril-like bundles consistent with collagen-like triple helices. This work predicts a number of CMP peptoid substitutions capable of forming stable triple-helical structures, presents a generalizable design strategy for engineering desired peptoid structures, and opens new avenues for the design of peptoid-based biomimetic materials.
This project was aimed at developing a thermophotovoltaic device that efficiently converts thermal radiation to electrical power. Historically, TPV devices have been plagued by poor robustness; this project sought to overcome this by merging innovations in nanophotonics, photovoltaics, and robust thermal engineering. Efforts were focused on developing high efficiency TPV devices which may drastically alter the electricity sector by enabling efficient (> 20%), fuel-flexible (any combustion fuel), distributed (< 10 kW) power generation. The project research identified the technical performance limits, technology differentiator, and customer value proposition for TPV devices and established technical performance requirements for a minimum viable product.
This report documents the improvements that have been made to the capabilities for coupling CTF to systems codes-specifically, the US Nuclear Regulatory Commission (NRC) TRACE code. An initial systems coupling capability had been set up previously using a nonoverlapping domain approach with the codes exchanging data at the core boundaries. The present work adds a new approach using overlapping domains, in which the system code models the core as well. A new input format has been added to allow the user to specify the physical quantities to be exchanged and their location in the system model, which gives the flexibility of applying one-way or two-way coupling between the codes using the desired data exchanges. In addition to applying thermal-hydraulics (T/H) boundary condition (BC) values obtained from TRACE, a capability was added to allow CTF to apply flow resistance feedback to TRACE to match the CTF core pressure drop. Support was added for executing parallel CTF models within the CTF-systems coupling. The system coupling capability was successfully applied to a parallel MSLB transient, demonstrating that both the one-way and two-way coupling behaved as expected and provided substantial improvements to numerical stability and routine compared to the previous nonoverlapping domain coupling. An initial capability was also developed for performing restart calculations in CTF which will be used in the future for restarting CTF-TRACE simulations at specific points in the transient simulation.
The nuclear industry is taking leaps in innovations with companies seeking a sustainable energy future through advanced nuclear reactors. The Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program seeks to substantiate and bolster the deployment of advanced reactors through flexible multifidelity, multiphysics simulations of advanced nuclear reactors. Applications like SAM for one-dimensional systems thermalhydraulics, and Pronghorn for multidimensional coarse mesh thermal-hydraulics, are geared to support innovations in industry by facilitating design, optimization, and licensing of advanced nuclear reactors. Coupling systems thermal-hydraulics and computational fluid dynamics codes can be difficult as the pressure coupling converges slowly; however, it is important to obtain the desired accuracy in each part of the primary loop. The authors of this model created an Overlapping-Domain Coupling (ODC) approach to coupling SAM and Pronghorn. Leveraging this coupling technique, a Molten Salt Reactor Experiment (MSRE) model was developed and released to the NEAMS/National Reactor Innovation Center (NRIC) Virtual Test Bed (VTB). The MSRE was chosen to be modeled because of the wealth of experimental data available and because of the strong physics coupling between the core and primary circuit. This paper contextualizes the history of the MSRE, describes the thermal hydraulics models used, and detail the implementation of multidimensional thermal-hydraulics and system codes based on the ODC method for the MSRE model. Finally, this paper presents how other modelers could apply the SAM Pronghorn ODC for other advanced reactor models.
Active insulation systems (AISs) refer to building envelopes with insulation materials that can change their thermal conductivity and are coupled with thermal mass to reduce building energy consumption and peak power. In this research, a novel optimal control approach is proposed to evaluate the maximum theoretical energy and cost-saving potential of AISs. A time-varying model predictive control (TV-MPC) controller was used to optimally select the AIS mode and simultaneously determine the operation of the heating, ventilation and air conditioning (HVAC) system so that the maximum saving potential of the entire system can be realized. To comprehensively evaluate the power shifting flexibility of AISs, two optimization objectives—minimizing weekly electric energy consumption and minimizing weekly electricity cost—were considered. The summer season simulation results show that under the first objective, more than 50% electric and thermal energy was saved when the upper boundary of the indoor air temperature was set to 25 °C. Furthermore under the second optimization objective, 38% of the cost was saved. It can be expected that the developed approach can be easily applied to multiple types of AISs with different mechanisms.
Here, we introduce a novel chance-constrained stochastic unit commitment model to address uncertainty in renewables' production uncertainty in power systems operation. For most thermal generators,underlying technical constraints that are universally treated as "hard" by deterministic unit commitment models are in fact based on engineering judgments, such that system operators can periodically request operation outside these limits in non-nominal situations, e.g., to ensure reliability. We incorporate this practical consideration into a chance-constrained stochastic unit commitment model, specifically by in-frequently allowing minor deviations from the minimum and maximum thermal generator power output levels. We demonstrate that an extensive form of our model is computationally tractable for medium-sized power systems given modest numbers of scenarios for renewables' production. We show that the model is able to potentially save significant annual production costs by allowing infrequent and controlled violation of the traditionally hard bounds imposed on thermal generator production limits. Finally, we conduct a sensitivity analysis of optimal solutions to our model under two restricted regimes and observe similar qualitative results.
Here we present a tomographic measurement of the cross-correlation between thermal Sunyaev-Zel’dovich (TSZ) maps from Planck and the Atacama Cosmology Telescope and weak galaxy lensing shears measured during the first three years of observations of the Dark Energy Survey. This correlation is sensitive to the thermal energy in baryons over a wide redshift range and is therefore a powerful probe of astrophysical feedback. We detect the correlation at a statistical significance of 21σ, the highest significance to date. We examine the TSZ maps for potential contaminants, including cosmic infrared background and radio sources, finding that cosmic infrared background has a substantial impact on our measurements and must be taken into account in our analysis. We use the cross-correlation measurements to test different feedback models. In particular, we model the TSZ using several different pressure profile models calibrated against hydrodynamical simulations. Our analysis marginalizes over redshift uncertainties, shear calibration biases, and intrinsic alignment effects. We also marginalize over Ω m and σ 8 using Planck or DES priors. We find that the data prefer the model with a low amplitude of the pressure profile at small scales, compatible with a scenario with strong active galactic nuclei feedback and ejection of gas from the inner part of the halos. When using a more flexible model for the shear profile, constraints are weaker, and the data cannot discriminate between different baryonic prescriptions.
The objectives of this SETO project are to explore whether photonic curing can be used to perform annealing in perovskite solar cell (PSC) fabrication, and if so, whether it can enable high-throughput PSC manufacturing. The successful outcome of the project will reduce manufacturing cost towards realizing the SETO goal of the Levelized cost of electricity (LCOE) $0.03/kWh by 2030. The project is a collaboration between Hsu’s group at the University of Texas at Dallas (UTD) and NovaCentrix, an Austin TX based company that pioneered the PulseForge® photonic curing tools and has expertise in applying this technology to printed electronics. Thin-film synthesis typically involves a thermal annealing step to convert from precursors to final material phases, to obtain the desired crystalline phase, or to improve materials structural or electrical properties. However, thermal annealing typically requires high temperatures that are incompatible with inexpensive plastic substrates and annealing times lasting tens-to-hundreds of minutes, making it incompatible with roll-to-roll (R2R) manufacturing at a desirable web speed. Photonic curing uses a flash Xe lamp to deliver short (20 µs to 100 ms) but high intensity (up to 50 kW/cm 2 ) pulses of broadband light (200 – 1500 nm) to the sample. It has been successfully applied to sinter printed metal nanoparticle inks into conductive patterns. This project aimed to extend the applications of photonic curing to convert halide perovskite films and transparent metal oxide transport layers. Despite the interruption by COVID-19, we have achieved significant accomplishments to establish photonic curing as a viable technology for the high-throughput manufacturing of PSCs. (1) We demonstrated that photonic curing can convert both metal oxide transport layer and halide perovskite absorber in the PSCs and successfully made flexible PSCs on Corning Willow glass® (WG)/ indium tin oxide (ITO) substrates without any thermal annealing steps. These photonically cured devices achieve performance comparable to conventional thermally annealed devices but were fabricated with a total processing time reduced by six orders of magnitude. We also show that photonic curing can achieve desirable web speed (up to 26 m/min) and large-area uniformity. (2) By establishing photonic curing processing phase spaces for the perovskite, we show that the longer pulses are more forgiving in small variation in the photonic curing conditions, making it more suitable for R2R manufacturing. (3) Our results clearly illustrated the importance of improving mechanical and optical properties of transparent electrodes on flexible substrates. (4) We also performed fundamental studies that elucidate the interactions between perovskite absorber and metal oxide transport layer that can undermine the PSC stability. Five refereed journal papers in top journals (ACS Energy Letters, npj Flexible Electronics, ACS Applied Energy Materials, Materials Advances, and Frontiers in Energy Research), one conference proceeding (PVSC-47), six conference presentations (PVSC and Materials Research Society meetings), and a Ph.D. dissertation (Trey B. Daunis) were produced under this project. Energy Materials Corporation (EMC) has forecast that with a 1.5 m wide web moving at a web speed of 30 m/min, R2R processing of PSC could provide up to 4 GW/year for a single R2R assembly line. Replacing thermal annealing with photonic curing, as demonstrated by the accomplishments of this project, is necessary to realize such an energy production goal.
The VTR is a 300-MW(thermal) sodium-cooled fast reactor (SFR) designed for the specific purpose of delivering unique testing capabilities to enable the advancement of all reactor technologies. With its flux level, irradiation volume, and operational flexibility, the VTR will enable accelerated testing of materials, fuels, and various components needing irradiation testing. Proven SFR technologies and design approaches have been leveraged in designing the VTR core, ensuring the highest possible readiness level. This resulted in the VTR using ternary metallic fuel and delivering fast flux levels in excess of 4 x 10 15 n/cm 2 ∙ s over large useful volumes, corresponding to about 60 dpa/year in steel. As part of the design efforts, the VTR core performance has been determined for a representative configuration, ensuring that the reactivity control systems offer sufficient shutdown margins, that the core can be safely cooled in all situations, and that reactivity feedback coefficients are conducive to a favorable safety behavior. Furthermore, the incorporation of features such as fuel assembly storage in the shield region supports the flexible and reliable operation of the VTR. Additional design work has been ongoing as well. This includes thorough shielding performance evaluations to ensure safe operation of the VTR, verification and validation of the design tools used to achieve compliance with Nuclear Quality Assurance (NQA-1) requirements, early assessment of the impact of irradiation experiments on the core performance envelope and associated margins, and in-depth uncertainty quantification efforts to quantify the anticipated range of performance characteristics. An experimental program supporting the VTR core design has been set up, with the current focus being on thermal-hydraulic experiments. The purpose of this experimental program is to obtain confirmatory measurements to serve directly as part of the core design basis or as part of the validation cases supporting the simulation tools used.