Combined Experimental and Modeling Study of Microwave-Assisted Methane Dehydroaromatization Process
ACS Fall Meeting 2022, Chicago, IL, August 21-25, 2022
Bai, Xinwei↗
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Component-Level Analysis of Heating and Cooling Loads in the U.S. Residential Building Stock
The residential building sector accounts for a substantial portion of total energy consumption in the United States and offers a significant opportunity for energy reduction and decarbonization through improvements in energy efficiency. Heating and air conditioning are the primary contributors to residential energy usage and electricity system peak demand. However, due to the diversity of the housing stock and the complexity of factors affecting heating and cooling demand, identifying the relative contributions to heating and cooling loads poses challenges. To address this, we applied the ResStock analysis tool to simulate 550,000 building energy models, providing statistical representation of residential buildings in the contiguous United States. We introduced outputs that quantified the heating and cooling influence of different components of a home, such as air leakage, envelope components (ceilings, walls, windows, foundations), internal heat gains from people, lighting, plug loads, and duct losses and gains. Leveraging the granularity of ResStock, we present a dataset to enable deeper understanding of the contributors to heating and cooling loads as a function of housing characteristics such as location, envelope efficiency, and building type. This work aims to support prioritization of research and development and informed decision-making for residential building decarbonization.
building simulation↗
Reward-Based Participant Management for Crowdsourcing Rainfall Monitoring: An Agent-Based Model Simulation
Crowdsourcing incorporates common citizens as rich sources of data and is promising for environmental monitoring. Here, we propose and test the idea of incorporating incentives to crowdsourcing management for rainfall monitoring. In particular, we model the allocation of incentives (quantitatively measurable and limited rewards) among crowdsourcing participants for a theoretical rainfall monitoring case. For this purpose, we develop an integrated model comprising a reward allocation component to represent the decision-making process of a central manager, an agent-based model to simulate the interactions between the manager and participants, and a rainfall simulation model to evaluate the effectiveness of various reward allocation policies. We simulate six reward allocation policies of varying levels of administrative cost, and consideration of participant and rainfall spatial heterogeneities. The findings indicate the performance of each policy to improve with the reward budget and their spatial uniformity. Among the six policies tested, we discover that the participant density weighted maximum participation policy yields the most accurate estimation of rainfall intensity due to its more explicit consideration of the spatial distribution of participants; however, this policy associates with a high administrative cost. This highlights the trade-off between performance and cost in designing effective reward allocation policies. This paper provides a physical and behavior simulation modeling tool to study the feasibility and complexity of reward-based participant management for crowdsourcing rainfall monitoring. The proposed crowdsourcing method is beneficial for a wide range of applications that require rainfall data with fine resolution, such as storm water management and water availability and biomass assessment for food and energy crops.
54 ENVIRONMENTAL SCIENCES↗
Characterizing uncertainty in Community Land Model version 5 hydrological applications in the United States
Abstract Land surface models such as the Community Land Model Version 5 (CLM5) are essential tools for simulating the behavior of the terrestrial system. Despite the extensive application of CLM5, limited attention has been paid to the underlying uncertainties associated with its hydrological parameters and how these uncertainties affect water resource applications. To address this long-standing issue, we use five meteorological datasets to conduct a comprehensive hydrological parameter uncertainty characterization of CLM5 over the hydroclimatic gradients of the conterminous United States. Key datasets produced from the uncertainty characterization experiment include: a benchmark dataset of CLM5 default hydrological performance, parameter sensitivities for 28 hydrological metrics, and large-ensemble outputs for CLM5 hydrological predictions. The presented datasets will assist CLM5 calibration and support broad applications, such as evaluating drought and flood vulnerabilities. The datasets can be used to identify the hydroclimatological conditions under which parametric uncertainties demonstrate substantial effects on hydrological predictions and clarify where further investigations are needed to understand how hydrological prediction uncertainties interact with other Earth system processes.
54 ENVIRONMENTAL SCIENCES↗
Oxygen solubility and transport in Li–air battery electrolytes: Establishing criteria and strategies for electrolyte design
Li–air or Li–oxygen batteries promise significantly higher energies than existing commercial battery technologies, yet their development has been hindered by a lack of suitable electrolytes. In this article, we evaluate the physical properties of varied electrolyte compositions to form generalized criteria for electrolyte design. We show that oxygen transport through non-aqueous electrolytes has a critical impact on the discharge rate and capacity of Li–air batteries. Through experiments and molecular dynamics simulations, we highlight that the choice of salt species and concentration have an outsized influence on oxygen solubility, while solvent choice is the major influence on oxygen diffusivity. The stability of superoxide reaction intermediates, key to the oxygen reduction mechanism, is also affected by variations in salt concentration and the choice of solvent. The importance of reactant transport is confirmed through Li–air cell discharge, which demonstrates good agreement between the observed and calculated mass transport-limited currents. Furthermore, these results showcase the impact of electrolyte composition on transport in metal–air batteries and provide guiding principles and simulation-based tools for future electrolyte design.
25 ENERGY STORAGE↗
Exploiting electricity market dynamics using flexible electrolysis units for retrofitting methanol synthesis
Here we investigate the economic viability of integrating flexible electrolysis units to produce hydrogen in methanol synthesis processes. Specifically, we investigate whether this approach can help reduce methanol production costs by strategically exploiting dynamics of electricity markets. Our study integrates high-fidelity process simulations, optimization tools, and microkinetic modeling (informed by density functional theory) to conduct detailed techno-economic analyses and to compare performance against traditional processes that use hydrogen produced via steam-methane reforming (SMR). We also use this approach to estimate the levelized cost of hydrogen (LCOH) as a function of time-varying electricity prices (from day-ahead and real-time prices) and of key techno-economic parameters. Our results show that the proposed electrification framework is cost-competitive under certain electricity market conditions. Specifically, we find that, when the electrolysis system is operated in flexible mode (and can respond to dynamics of electricity markets), the associated electricity cost nearly collapses to zero. Conversely, when the unit is not flexible (and cannot respond to markets), the electricity cost comprises 60% of the total cost. Our results also reveal that the LCOH of the flexible electrolysis system participating in real-time electricity markets is 31% lower than the LCOH obtained from SMR. Overall, this indicates that exploiting the dynamics of electricity markets can make hydrogen production cost-competitive and this can lead to viable alternatives to electrify methanol production and other hydrogen-based processes.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Enhancing Drinking Water Quality Modeling: Leveraging Physics Informed Neural Networks for Learning with Imperfect Reaction Models and Partial Data
Chemical kinetics models, typically formulated as systems of ordinary or partial differential equations, are valuable tools for simulating drinking water quality. However, these models often face inaccuracies due to discrepancies between the laboratory and the real-world conditions, as well as limitations in experimental analytical methods, hindering the accurate representation of the true underlying chemical mechanisms. In this study, we propose a Physics Informed Neural Network (PINN), using the eXtreme Theory of Functional Connections, to improve the prediction of chemical concentrations over time. The PINN method accounts for imperfect chemical models and incorporates partial data to improve predictions. Focusing on reactions describing water disinfection residual and disinfectant byproduct formation, which are crucial for public health and regulatory compliance, we demonstrate that the PINN model is able to accurately predict the concentrations of chemical species across various pH values. Notably, the model extends its accuracy to predict concentrations of chemical species not originally included in its training data. The developed method can be extended to a variety of chemical systems, offering a wide array of potential applications.
13 HYDRO ENERGY↗
Coordinative Real-time Sub-Transmission Volt-VAr Control for Reactive Power Regulation between Transmission and Distribution Systems
This paper introduces an integrated voltage regulation approach to coordinate the Volt-VAr control between transmission and distribution systems. Distributed photovoltaic (PV) systems are aggregated as a virtual power plant (VPP). At the sub-transmission level, a Coordinated Real-time Sub-Transmission Volt-VAr Control Tool (CReST-VCT) is introduced to coordinate the operation of the shunt devices and the reactive power provided by the VPPs. The CReST-VCT uses an enhanced Volt-VAr control algorithm with weighted voltage control objects that include minimizing losses, maintaining the voltage within desirable levels, and minimizing the number of mechanical switching of shunt elements. The algorithm runs every 5 minutes and is solved using AC optimal power flow (OPF) solution technique. The outputs include the settings for each sub-transmission-level Volt-VAr control devices and the reactive power generation requirements for each VPP. Then, each VPP will run a distribution Volt-VAr control algorithm to select the PV inverters that provide the Volt-VAr control services considering the distribution network topology. The goal of the VPP reactive power control is to meet the transmission level service requirements while maintaining the voltage and line flow in the distribution system within limits. Each VPP will update its voltage regulation capacity every 5 minutes to allow the CReST-VCT to formulate the optimization problem for the next dispatch interval. The proposed tool is simulated on Duke Energy Carolina system to demonstrate the capability of providing voltage support service by dispatching of reactive power of distributed PV as VPP.
Ke, Xinda↗
Data Reliability in BIM and Performance Analytics: A Survey of Contemporary AECO Practice
As awareness around building energy consumption increases, practitioners are encouraged to consider performance aspects regarding the built environment more closely and find ways to improve its efficiency. Improvements in building information modeling (BIM) and building performance simulation (BPS) tools present opportunities to facilitate information communication with a wider range of stakeholders. The building sector can benefit from the integration of performance informatics; however, there has been limited success in utilizing available technologies that promote data integration and management in favor of enriching our knowledge and understanding of buildings as artifacts of information. This phenomenon was investigated by conducting a survey, together with a review of relevant literature, to depict the relevant challenges and opportunities for the architecture, engineering, construction, and owner-operated (AECO) industry, as it undergoes digital transformation, as well as the working practices that have formed around them. It is argued that the current tools available to practitioners do not support effective data serialization between design and analytics processes, affecting the collaboration between team members. Lastly, a series of functional goals are proposed to support a higher level of reliability in the ways information is mobilized, by rethinking the technologies and methods for organizing information systems.
42 ENGINEERING↗
Stationary state distribution and efficiency analysis of the Langevin equation via real or virtual dynamics
Langevin dynamics has become a popular tool to simulate the Boltzmann equilibrium distribution. When the repartition of the Langevin equation involves the exact realization of the Ornstein-Uhlenbeck noise, in addition to the conventional density evolution, there exists another type of discrete evolution that may not correspond to a continuous, real dynamical counterpart. This virtual dynamics case is also able to produce the desired stationary distribution. Different types of repartition lead to different numerical schemes, of which the accuracy and efficiency are investigated through studying the harmonic oscillator potential, an analytical solvable model. By analyzing the asymptotic distribution and characteristic correlation time that are derived by either directly solving the discrete equations of motion or using the related phase space propagators, it is shown that the optimal friction coefficient resulting in the minimum characteristic correlation time depends on the time interval chosen in the numerical implementation. In conclusion, when the recommended “middle” scheme is employed, both analytical and numerical results demonstrate that, for good numerical performance in efficiency as well as accuracy, one may choose a friction coefficient in a wide range from around the optimal value to the high friction limit.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Making many-body interactions nearly pairwise additive: The polarized many-body expansion approach
The Many-Body Expansion (MBE) is a useful tool to simulate condensed phase chemical systems, often avoiding the steep computational cost of usual electronic structure methods. However, it often requires higher than 2-body terms to achieve quantitative accuracy. In this work, we propose the Polarized MBE (PolBE) method where each MBE energy contribution is treated as an embedding problem. In each energy term, a smaller fragment is embedded into a larger, polarized environment and only a small region is treated at the high-level of theory using embedded mean-field theory. The role of polarized environment was found to be crucial in providing quantitative accuracy at the 2-body level. PolBE accurately predicts noncovalent interaction energies for a number of systems, including CO 2 , water, and hydrated ion clusters, with a variety of interaction mechanisms, from weak dispersion to strong electrostatics considered in this work. We further demonstrate that the PolBE interaction energy is predominantly pairwise unlike the usual vacuum MBE that requires higher-order terms to achieve similar accuracy. We numerically show that PolBE often performs better than other widely used embedded MBE methods such as the electrostatically embedded MBE. Finally,owing to the lack of expensive diagonalization of Fock matrices and its embarrassingly parallel nature, PolBE is a promising way to access condensed phase systems with hybrid density functionals that are difficult to treat with currently available methods.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Self-consistent integrated modeling of combined hybrid discharge-laser produced plasma devices for extreme ultraviolet metrology
Discharge- and laser-produced plasma (DLPP) devices are being used as light sources for extreme ultraviolet (EUV) generation. A key challenge for both, DPP and LPP, is achieving sufficient brightness to support the throughput requirements of nanometrology tools. To simulate the environment of a hybrid DLPP device and optimize the EUV output, we have developed an integrated HEIGHTS-DLPP computer simulation package. The package integrates simulation of two evolving plasmas (DPP and LPP) and includes modeling of a set of integrated self-consistent processes: external power source and plasma energy balance, plasma resistive magnetohydrodynamics, plasma heat conduction, detailed radiation transport (RT), and laser absorption and refraction. We simulated and optimized DLPP devices using Xe gas as a target material. We synchronized the external circuit parameters, chamber gas parameters, and laser beam temporal and spatial profiles to achieve maximum EUV output. The full 3D Monte Carlo scheme was integrated for detailed RT and EUV output calculations in Xe using more than 3600 spectral groups. The modeling results are in good agreement with Julich Forschungszentrum experimental data. Theoretical models, developed and integrated into the HEIGHTS package, showed wide capabilities and flexibility. In conclusion, the models and package can be used for optimization of the experimental parameters and settings, investigation of DLPP devices with complex design, analyzing the impact of integrated spatial effects and working timeline arrangement on the final EUV output, and EUV source size, shape, and angular distribution.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
On the detectability of the moving lens signal in CMB experiments
Abstract Upcoming cosmic microwave background (CMB) experiments are expected to detect new signals probing interaction of CMB photons with intervening large-scale structure. Among these the moving-lens effect, the CMB temperature anisotropy induced by cosmological structures moving transverse to our line of sight, is anticipated to be measured to high significance in the near future. In this paper, we investigate two possible strategies for the detection of this signal: pairwise transverse-velocity estimation and oriented stacking. We expand on previous studies by including in the analysis realistic simulations of competing signals and foregrounds. We confirm that the moving lens effect can be detected at ≥ 10σlevel by a combination of CMB-S4 and LSST surveys. We show that the limiting factors in the detection depend on the strategy: for the stacking analysis, correlated extragalactic foregrounds, namely the cosmic infrared background and thermal Sunyaev Zel'dovich effect, play the most important role. The addition of foregrounds make the signal-to-noise ratio be most influenced by large and nearby objects. As for the pairwise detection, halo lensing and pair number counts are the main issues. In light of our findings, we elaborate on possible strategies to improve the analysis approach for the moving lens detection with upcoming experiments. We also deliver to the community all the simulations and tools we developed for this study.
Astronomy & Astrophysics↗
Neural net modeling of equilibria in NSTX-U
Neural networks (NNs) offer a path towards synthesizing and interpreting data on faster timescales than traditional physics-informed computational models. In this work we develop two NNs relevant to equilibrium and shape control modeling, which are part of a suite of tools being developed for the National Spherical Torus Experiment-Upgrade for fast prediction, optimization, and visualization of plasma scenarios. The networks include Eqnet, a free-boundary equilibrium solver trained on the EFIT01 (Equilibrium FITtting 01) reconstruction algorithm, and Pertnet, which is trained on the Gspert code and predicts the non-rigid plasma response, a nonlinear term that arises in shape control modeling. The NNs are trained with different combinations of inputs and outputs in order to offer flexibility in use cases. In particular, Eqnet can use magnetic diagnostics as inputs and act as an EFIT-like reconstruction algorithm, or, by using pressure and current profile information the NN can act as a forward Grad–Shafranov equilibrium solver. This forward-mode version is envisioned to be implemented in the suite of tools for simulation of plasma scenarios. The reconstruction-mode version gives some performance improvements compared to the online reconstruction code real-time EFIT, especially when vessel eddy currents are significant. Here, we report strong performance for all NNs indicating that the models could reliably be used within closed-loop simulations or other applications. Some limitations are discussed.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Hybrid power plant design for low-carbon hydrogen in the United States
In this study, we provide a nationwide techno-economic analysis of clean hydrogen production powered by a hybrid renewable energy plant for over 50,000 locations in the United States. We leverage the open-source Hybrid Optimization Performance Platform (HOPP) tool to simulate the hourly performance of an off-grid wind-solar plant integrated with a 1-GW polymer exchange membrane electrolyzer system. The levelized cost of hydrogen is calculated for varying technology costs, and tax credits to explore cost sensitivities independent of plant design, performance, and site selection. Our findings suggest that strategies for cost reduction include selecting sites with abundant wind resources, complementary wind and solar resources, and optimizing the sizing of wind and solar assets to maximize the hybrid plant capacity factor. These strategies are linked to increased hydrogen production and reduced electrolyzer stack replacements, thereby lowering the overall cost of hydrogen.
08 HYDROGEN↗
Continuous variable port-based teleportation
Abstract Port-based teleportation (PBT) is a generalisation of the standard teleportation protocol which does not require unitary operations by the receiver. This comes at the price of requiring N > 1 entangled pairs, while N = 1 for the standard teleportation protocol. The lack of correction unitaries allows PBT to be used as a fundamental theoretical tool to simulate arbitrary channels with a general resource, with applications to study fundamental limits of quantum communication, cryptography and sensing, and to define general programmable quantum computers. Here we introduce a general formulation of port-based teleportation in continuous variable systems and study in detail the N = 2 case. In particular, we interpret the resulting channel as an energy truncation and analyse the kinds of channels that can be naturally simulated after this restriction.
97 MATHEMATICS AND COMPUTING↗
Production of energetic light fragments in extensions of the CEM and LAQGSM event generators of the Monte Carlo transport code MCNP6 [Production of energetic light fragments in CEM, LAQGSM, and MCNP6]
We extend the cascade-exciton model (CEM), and the Los Alamos version of the quark-gluon string model (LAQGSM), event generators of the Monte Carlo N-particle transport code version 6 (MCNP6), to describe production of energetic light fragments (LF) heavier than 4 He from various nuclear reactions induced by particles and nuclei at energies up to about 1 TeV/nucleon. In these models, energetic LF can be produced via Fermi breakup, preequilibrium emission, and coalescence of cascade particles. Initially, we study several variations of the Fermi breakup model and choose the best option for these models. Then, we extend the modified exciton model (MEM) used by these codes to account for a possibility of multiple emission of up to 66 types of particles and LF (up to 28 Mg) at the preequilibrium stage of reactions. Then, we expand the coalescence model to allow coalescence of LF from nucleons emitted at the intranuclear cascade stage of reactions and from lighter clusters, up to fragments with mass numbers A ≤ 7, in the case of CEM, and A ≤ 12, in the case of LAQGSM. Next, we modify MCNP6 to allow calculating and outputting spectra of LF and heavier products with arbitrary mass and charge numbers. The improved version of CEM is implemented into MCNP6. Lastly, we test the improved versions of CEM, LAQGSM, and MCNP6 on a variety of measured nuclear reactions. The modified codes give an improved description of energetic LF from particle- and nucleus-induced reactions; showing a good agreement with a variety of available experimental data. They have an improved predictive power compared to the previous versions and can be used as reliable tools in simulating applications involving such types of reactions.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Isometric Tensor Network States in Two Dimensions
Tensor-network states (TNS) are a promising but numerically challenging tool for simulating two-dimensional (2D) quantum many-body problems. We introduce an isometric restriction of the TNS ansatz that allows for highly efficient contraction of the network. Here we consider two concrete applications using this ansatz. First, we show that a matrix-product state representation of a 2D quantum state can be iteratively transformed into an isometric 2D TNS. Second, we introduce a 2D version of the time-evolving block decimation algorithm for approximating of the ground state of a Hamiltonian as an isometric TNS-which we demonstrate for the 2D transverse field Ising model.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗