Modeling investment decisions from heterogeneous firms under imperfect information and risk in wholesale electricity markets
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The intermittency of carbon-free renewables and the demand changes associated with the widespread push for electrifying the transportation and building sectors provides an opportunity for buildings to go beyond energy efficiency and push towards providing demand flexibility to the electricity grid. The duality of energy efficiency and demand flexibility is necessary for success in a sustainable and reliable energy transition. Current building energy benchmarking models are limited in their ability to integrate concepts of demand flexibility and/or utilize granular smart meter data. Thus, current benchmarking methods are focused annual energy usage and fail to incorporate how the time of use of energy consumption impacts emissions in a quickly changing energy grid. Without a more comprehensive view of energy usage and associated real-time emissions, current benchmarking methods are unlikely to realize the full decarbonization potential of buildings. New emerging data streams provide an opportunity to develop a new generation of benchmarking energy models that embed dimensions of energy efficiency, grid interactivity, and demand flexibility into their analysis. In this paper, we propose a four-step method for embedding grid interactivity and demand flexibility into building benchmarking models that utilizes emerging building and time-series electricity data streams. We first engineer features to produce a mix-type dataset that encompasses many attributes of grid-interactive and efficient buildings, and then we apply K-medoids using Gower's Distance to produce peer-group clusters. We apply the method to a case study of 306 primary and secondary schools in southern California, USA. The results show that the method effectively clusters buildings by attributes of demand flexibility and energy efficiency. The clustering results reveal patterns in inefficient building operations and demand inflexibility at the building peer group level. In conclusion, the interpretation of clusters can serve as an integrated energy efficiency and demand flexibility benchmarking model and inform performance-specific policy targeting for buildings that go beyond traditional efficiency measures.
Concerns over the land use changes impacts of solar photovoltaic (PV) development are increasing as PV energy development expands. Co-locating utility-scale solar energy with vegetation may maintain or rehabilitate the land's ability to provide ecosystem services. Previous studies have shown that vegetation under and around the panels may improve the performance of the co-located PV and that PV may create a favorable environment for the growth of vegetation. While there have been some pilot-scale experiments, the existence and magnitude of these benefits of vegetation has not been confirmed in a utility-scale PV facility over multiple years. In this study we use power output data coupled with microclimatic measurements in temperate climates to assess these potential benefits. Here this study combines multi-year microclimatic measurements to analyze the physical interactions between PV arrays and the underlying soil-vegetation system in three utility-scale PV facilities in Minnesota, USA. No significant cooling of PV panels or increased power production was observed in PV arrays with underlying vegetation. Fine soil particle fraction was the highest in soils within PV arrays with the vegetation which was attributable to the lowest wind speeds from the compounding suppression of wind by vegetation and PV arrays. Soil moisture and soil nutrient response to re-vegetation varied between PV facilities, which could be attributed to differing soil texture. No statistically significant vegetation-driven panel cooling was observed in this climate. This finding prompts a need for site-specific studies to identify contributing factors for environmental co-benefits in co-located systems.
The customized production of complex components by 3D printing has been hailed as a potentially transformative tool in manufacturing with important applications in health care, automotive and aerospace industries. However, after about a quarter of a century of research and development, only a handful of commercial alloys can be printed and the market value of all 3D printed products now amounts to a negligible portion of the manufacturing economy. This difficulty is attributable to a remarkable diversity in structure and properties of the printed components and susceptibility to defects. In addition, the current practice of qualifying components by prolonged trial and error with expensive printing equipment and feed stock material confine the printed products to a niche market where the high product cost and the delay in the qualification are not critical factors. In this report we explain how a digital twin or a digital replica of the printing machine will reduce the number of trial and error tests to obtain desired product attributes and reduce the time required for part qualification to make the printed components cost effective. It is shown that a comprehensive digital twin of 3D printing machine consisting of mechanistic, control and statistical models of 3D printing, machine learning and big data can reduce the volume of trial and error testing, reduce defects and shorten time between the design and production.
There exist substantial differences in top-of-atmosphere direct radiative forcing of aerosols due to a region's economic production (RFp) and consumption (RFc), in the context of economic globalization, trade and globalizing air pollution. Yet an explicit systematic analysis of all socioeconomic and atmospheric factors determining the RF difference is lacking. Here, we evaluate five socioeconomic (population, per capita output, emission intensity) and atmospheric (chemical efficiency and radiative efficiency) factors that determine a region's RFp, RFc and their difference. We consider the RF of secondary inorganic aerosols, primary organic aerosols and black carbon by 10 regions worldwide in 2007. The population size varies by a factor of nine across the regions, and per capita output by 40 times from both production- and consumption-based perspectives. The cross-regional spread reaches a factor of 181 (species dependent) for production-based emission intensity and a factor of 96 for consumption-based intensity. From one region to another, production-based chemical efficiency changes within a factor of 5 and consumption-based efficiency within a factor of 3.5. Radiative efficiency varies slightly across the regions (within 2) from both production- and consumption-based perspectives. Although socioeconomic factors are often a greater driver for the difference between a source region's RFp and RFc, the atmospheric factors are also important for many source regions and species. Our results contribute to regional attribution of climate change and establishment of effective international collaborative mitigation strategies.
We report agent-based modeling is an advanced computational technique capable of representing complex and dynamic processes of human behavior in building performance simulation. Though the agent-based approach supports diverse applications concerning human behavior modeling within the built environment, there is no consensus on the optimal amount of information or level of granularity needed for occupant information representation. This paper attempts to formalize the level of details (LoD) needed for occupant behavior representation in agent-based environments. A novel framework, grounded on the concept of LoD, is proposed to select the required details in representing occupants in agent-based models. Ten attributes related to occupants' presence, movement, behavioral processes, and repertoire are considered to define the LoD. The framework identifies use case parameters as the guiding principle and allows a hybrid approach for selecting varying degrees of occupant attributes to serve the purpose of simulation. A discussion on the pertinence of different occupant behavior LoDs in relation to the desired objective and simulation context is also presented. The study intends to support the occupant behavior research by advancing agent-based occupant modeling in building performance simulation.
Highlights: • Hyperhomocysteinemia attenuates PI3K-AKT & WNT signalling and manifests PCOS-like phenotypes in rats. • Hyperhomocysteinemia promotes StAR and atenuates Aromatase expression, and thereby leads to hyperandrogenemia. • Hyperandrogenemia and hyperhomocysteinemia share PCSK9-LDLR pathway and independently induce atherogenic dyslipidemia. • Because of hyperandrogenemia, PCOS patients are inherently at increased risk of cardiovascular disease. • Association of HHcy further aggravates the cardiovascular risk in PCOS. Women with polycystic ovary syndrome (PCOS) are at increased risk of cardiovascular diseases (CVD); however, the independent role of PCOS in the incident CVD remains unknown. There are reports that hyperhomocysteinemia (HHcy), a potential cause of CVD, is frequently associated with PCOS. The present study investigates the independent attributes of hyperandrogenemia (HA), the integral associate of PCOS, and HHcy in causing atherogenic dyslipidemia. Twenty-five-day old rats were treated with homocysteine (Hcy) at 50 mg/kg/day dose level for 12 weeks. The HepG2 cell lines transfected with siRNA directed to PCSK9 were challenged with Hcy, homocysteine thiolactone (HTL), testosterone, 5α-dihydroxytestosterone (5α-DHT), or estradiol for 24 h. Rats administered with Hcy developed HHcy and displayed PCOS-like phenotypes with adversely altered lipid homeostasis and attenuated PI3K-AKT and Wnt signalling cascade. Overexpression of steroidogenic acute regulatory protein (StAR) and down-regulated expression of Aromatase together with elevated testosterone level marked the state of HA. In culture, the HepG2 cells responded independently to Hcy, HTL, testosterone, and 5α-DHT by an overt expression of PCSK9 and down-regulated expression of LDLR. The effect was magnified under the combined influence of Hcy and androgen(s). Estradiol, by contrast, exhibited the reverse effect. The findings suggest that HA may independently attribute to an increased cardiovascular risk in PCOS; however, the coexistence of HHcy catalyzes the risk further.
Highlights: • The Nlrp3 inflammasome is activated by ROS during lung ischemia-reperfusion. • Mcc950 blocks Nlrp3 inflammasome activation and protects against lung ischemia-reperfusion injury. • The mechanism of Mcc950 is partially attributed to inhibition of the interaction between Nlrp3 and Nek7. Lung ischemia-reperfusion (IR) occurs in many circumstances and leads to impaired lung function. The NACHT, LRR and PYD domains-containing protein 3 (Nlrp3) inflammasome is reportedly activated during lung IR. Mcc950 is a recently developed Nlrp3 inhibitor. The aim of our study was to test the efficacy of Mcc950 on lung IR injury and to investigate the role of reactive oxygen species (ROS) in Nlrp3 inflammasome activation using a murine lung IR model. The results of the current study confirmed that Nlrp3 was upregulated and activated during lung IR, and inhibiting oxidative stress by the ROS scavenger edaravone attenuated Nlrp3 inflammasome activation. Mcc950 pretreatment significantly alleviated IR-induced lung injury by reducing production of the proinflammatory cytokines Il-1β and Il-18 and inhibiting neutrophil infiltration and cell apoptosis. Protein coimmunoprecipitation revealed that Mcc950 partially blocked the interaction between Nlrp3 and Nek7 (NimA-related protein kinase 7). Therefore, we conclude that ROS-dependent activation of the Nlrp3 inflammasome contributed to lung IR injury. Mcc950 significantly reduced lung IR injury by blocking Nlrp3 inflammasome activation, and the mechanism was partially attributed to inhibition of the interaction between Nlrp3 and Nek7. Thus, Mcc950 is a promising treatment for the prevention of lung IR injury.
A discrete element method (DEM) based approach is used to study the relationships between material attributes (MAs), processing parameters (PPs), and quality attributes (QAs) for the knife milling of maize stalks. An approximate DEM shape model was conceptualized based on real maize stalks and calibrated based on experimental bending test data for flexural properties (elastic bending stiffness, elastic bending angle limit, elastoplastic ratio, etc.). DEM simulations of maize stalk comminution in a Jordan Reduction Solutions (“JRS”) knife mill were performed to investigate the relationships between the MAs (maize stalk size and breakage stress limit), PPs (impeller rotational speed), and QAs (mass throughput and output particle size distribution (PSD)). The DEM results suggest that stalk length has little influence on mass throughput and PSD, whilst stalks with larger cross sections tend to generate larger sizes of milled particles given the same breakage stress limit. Both the DEM and experimental results show that faster impeller rotation (or higher power) does not necessarily generate higher throughput or smaller output PSD, especially for maize stalks of higher breakage stress limit. The correlations between these MAs, PPs and QAs are found highly stochastic, though breakage stress limit dictates mass throughput, regardless of stalk size. The DEM-predicted output particle size tended to match the experimental data with coarse PSDs based on sieve size but showed weakened fidelity with finer material, indicating the potential for further model improvement.
The kinetics for O 2 oxidation of individual graphite and graphene platelet nanoparticles (NPs) were studied as a function of temperature (1200 to 2200 K) at varying oxygen partial pressures, using a single nanoparticle mass spectrometry method. NP temperature (TNP) was measured by measuring the NP thermal emission spectra during the kinetics studies. The initial oxidation efficiency is found to peak in the 1200 to 1500 K range, dropping by an order of magnitude as TNP was increased above 2000 K. There were large NP-to-NP variations in the oxidation rates, attributed to variations in the NP surface structure. In addition, the oxidation efficiencies evolved, non-monotonically, as the NPs reacted, decreasing by factors of between 10 and 300. This evolution of reactivity is attributed to changes in the NP surface structure due to the combination of oxidation and annealing. In conclusion, the optical properties, including wavelength dependence of the emissivity and the absorption cross section for the 532 nm heating laser, also tended to evolve as the NPs oxidized, but differently for each individual NP, presumably reflecting differences in the initial structures and their evolution.
Designing materials with low thermal conductivity is a crucial objective for applications in thermal insulation and thermoelectrics. Traditional methods such as doping, mechanical strain and introducing defects in perfect crystals have been widely explored to impede the flow of heat. Here, this work introduces dimensional constriction and cationic disorder as novel avenues to manipulate lattice thermal conductivity (LTC). High entropy materials characterized by random distribution of multiple elements, creates a suitable environment for thermal insulation due to its configurational disorder and local lattice distortions. On the other hand, MXenes, derived from MAX-phase, have garnered considerable attention due to their unique structural attributes, leading to potential applications in catalysis and energy storage. Ti 2 AlC MAX-phase is examined to understand the impact of dimensional constriction on phonon transport of Ti 2 C with cationic disorder, i.e., (Ti 0.25 Nb 0.25 Cr 0.25 Ta 0.25 ) 2 C. The exponential reduction in LTC of HE-MXene is attributed to disorder scattering that significantly limits phonon mean free path (MFP) and relaxation time. The spread of mode-resolved LTC with MFP highlights the influence of disorder on phonon scattering. This work provides a systematic approach to engineer LTC through dimensional constriction and cationic disorder, laying the foundation for tailored materials with desired thermal properties.
Effective design of heterogeneous catalytic systems requires careful coordination of physiochemical phenomena that span orders or magnitude in length and time scales. Multiscale modelling and simulation tools can provide useful insight for understanding and improving the performance of such systems. Mesoporous silica catalyst support materials present a versatile platform wherein support attributes may be tuned to control transport phenomena throughout the system. In this study we develop an integrated multiscale modelling approach for the conversion of ethanol to butadiene over a SBA-16 mesoporous silica supported catalyst. We use molecular dynamics simulations to calculate domain specific diffusivities of reactants and products in the various domains of SBA-16's nanostructure. This is used to calculate a resultant effective diffusivity through its microstructure using finite element method (FEM) models of the tessellated unit cell. The resultant intraparticle effective diffusivity enables the development of a reduced-order reactor level FEM model that is able to implicitly account for the SBA-16's transport effects without the explicit consideration of its detailed geometry. Experimental bench-scale conversion data for the ethanol to butadiene process over SBA-16 is used to extract intrinsic kinetic rate constants for a simplified reaction mechanism using this reduced order bench-scale reactor FEM model. The model is able to reproduce experimental trends in conversion and activity lifetimes. The impact of varying key support attributes such as pore-size and particle size on catalytic activity lifetimes is then explored. We demonstrate the utility of this multi-scale modelling strategy in guiding catalyst design for the development of rational strategies to improve the performance of heterogeneous supported catalytic systems.
This study quantifies NO{sub x} uptake efficiency and explores NO{sub x} binding mechanisms in calcium aluminate cementitious (CAC) materials. Comparison between unmodified and TiO{sub 2}-modified CAC separates intrinsic NO{sub x} binding mechanisms from those related to photocatalysis. Attributed to surface-related heterogeneous reactions, the NO{sub x} binding occurs in unmodified CAC at nitrite-to-nitrate ratio of 1: 1.3 and can be increased with surface area. The photocatalytic reactions in TiO{sub 2}-modified CAC increase NO{sub x} uptake, and ~50% of converted NO{sub x} resists releasing back into the environment via dissolution. Compared to previously studied ordinary portland cement (OPC) materials, CAC increases NO{sub x} uptake capacity and demonstrates a more permanent NO{sub x} binding, potentially mitigating concerns related to the release of previously bound N-species in OPC. Examination of the interaction between NO{sub x} and a synthetic pure aluminum-bearing phase shows that the permanent NO{sub x} uptake in CAC could be largely attributed to the chemical binding of converted NO{sub x} within aluminum-bearing phases.
It has been well recognized that the benefits and effectiveness of nanoparticles in cement-based materials could not be maximized if these are not well dispersed. To address this issue, in this study, different anionic (SDS and PCE) and nonionic surfactants (Tweens and Tritons) were used to disperse nanosilica (NS) in aqueous solution and cement pore solution. The results show that the dispersibility of NS in cement pore solution was improved, and the compressive strength of the cement-NS pastes increased linearly with critical micelle concentration (CMC) of nonionic surfactants. Among all surfactants studied, Triton X-405 led the paste to the highest increase in strength (33% at 1-day and 41% at 3-days) since it had the highest CMC. TEM and EDS analysis evidenced that this strength increase might be attributed to the nucleation of outer product CSH gel and its densification with calcite nanocrystals, attributed to Triton X-405 addition.
This study reports on the sintering and oxidation behaviors of Hafnium Diboride (HfB 2 ) and Hafnium Carbide (HfC) based ultra-high temperature ceramic (UHTC) composites. Pure Hafnium Diboride, Hafnium Carbide, and HfB 2 -50 vol% HfC composite were consolidated using spark plasma sintering (SPS) without the use of sintering aids. HfB 2 -HfC composite displayed a high sintered density of 98% as compared to 87% density of pure HfB 2 . The increased density of the HfB 2 -HfC composite is attributed to the bimodal powder distribution, which allowed for the smaller HfC particle to occupy the voids between the larger HfB 2 particles resulting in improved packing efficiency. Moreover, the higher planar surface energy, for the (111) and the (200) planes for HfC, contributed to the smaller HfC particle being a significant driving force in the sintering process. Oxidation studies of each material were carried out by exposing them to a high-speed plasma jet in a temperature exceeding 2700 °C. The results of these studies show an improved oxidation resistance of HfB 2 -HfC composite by 54% and 70% over pure HfC and HfB 2 , respectively. The enhanced oxidation behavior is attributed to B 2 O 3 filling in the porosity between the HfO 2 scale and protecting the underlying material. This study provides a new alternative to improve the sinterability of UHTC diborides by introducing another UHTC (i.e., HfC) to form a fully dense composite without sintering aid and superior oxidation resistance.
The emergence of a new class of high entropy ultra-high temperature ceramics (HE-UHTCs) is expected to possess exceptionally superior mechanical, oxidation, and erosion resistance as compared to conventional UHTCs. The improvement in the properties of HE-UHTCs is attributed to the high configurational entropy of the multi-component system stabilized into a single-phase, but with little discussion on entropy contributions. This perspective article presents a viewpoint on the critical scientific question regarding the actual role entropy plays in stabilizing and enhancing the thermo-mechanical properties of a multi-component system. The high throughput first-principle calculations, which can provide the entropy formation ability (EFA) of thermodynamically stable HE-UHTCs, can prove to be valuable toolset to this puzzle. HE-UHTCs show enhancement in the mechanical properties much higher than the predicted rule of the mixture, which cannot traditionally be explained by a mere solid solution formation effect. Additionally, isothermal oxidation studies of HE-UHTCs limited to furnace testing state remarkable oxidation resistance which is attributed to the passivity of complex, layered structure, and composition of the oxide scale. However, whether all the constituents in the HE-UHTC system react simultaneously or preferential oxidation takes place needs to be addressed. To address all these issues, an integrated computational and experimental approach has been postulated towards designing a thermal protection system (TPS) for re-entry applications. Succeeding the approach will provide new opportunities in the compositional space of HE-UHTCs with tailored properties.
Ultra-high temperature ceramics (UHTCs) have shown aspiration to overcome challenges in the thermal protection system (TPS) by designing new materials referred to as multi-component UHTCs (MC-UHTCs) in the compositional space. MC-UHTCs have shown remarkable improvement in oxidation resistance due to the formation of the Hf6Ta2O17 superstructure during plasma exposure. Herein, the Hf 6 Ta 2 O 17 superstructure is synthesized via a solid-state reaction between HfO 2 and Ta 2 O 5 powder mixtures during spark plasma sintering (SPS). The compositions chosen are 50 vol% of HfO 2 -50 vol% of Ta 2 O 5 (50HO-50TO) and 70 vol% of HfO 2 -30 vol% of Ta 2 O 5 (70HO-30TO). The phase quantification via Rietveld analysis showed Hf 6 Ta 2 O 17 as a principal phase with some residual Ta 2 O 5 phase in both the samples. The high-temperature thermal stability of the samples was evaluated using high-velocity plasma jet exposure for up to 3 min. 50HO-50TO was able to withstand the intense plasma condition, which is attributed to the higher content of the Hf 6 Ta 2 O 17 phase (~84%) and lower strain in the Ta 2 O 5 phase. The augmentation in the Hf 6 Ta 2 O 17 phase to 94.7% (in 50HO-50TO) post plasma exposure has been attributed to the invariant transformation from a liquid state to Hf 6 Ta 2 O 17 at temperatures >2500 °C during testing. The mechanical integrity is elucidated from the insignificant change in the hardness ~13.3 GPa before and 11.2 GPa after plasma exposure of the 50HO-50TO sample. As a result, the Hf 6 Ta 2 O 17 superstructure's thermo-mechanical stability suggests developing novel oxidation-resistant MC-UHTCs in compositional space for reusable space vehicle applications.
The sorption of aqueous Mn(II) (1 mM) and Co(II) (50 and 200 μM) onto hexagonal birnessite (0.1 g L –1 ) was studied under anoxic conditions at pH 6.5 and 7.5 in binary and ternary experiments using batch kinetic experiments and XRD, ATR-FTIR, and Co K-edge EXAFS analyses. In the binary systems, sorption of Co(II) was accompanied by partial oxidation to Co(III) yielding a mixture of corner-sharing Co(II) and edge-sharing Co(III) complexes at both pH values, while Mn(II)-birnessite interaction resulted in coordination of Mn(II/III) at layer vacancy sites at pH 6.5, and led to reductive transformation of birnessite into feitknechtite at pH 7.5. In the ternary systems, strong mutual interferences between Co(II) and Mn(II) co-sorbates reduced the rate and extent of sorption relative to the binary experiments. The introduction of Mn(II) aq into the high-Co systems (200 μM) halted the slow sorption of Co(II) that was attributed to the incorporation of Co(III) into layer vacancies, while Co(II) aq prevented Mn(II)-driven transformation of birnessite into feitknechtite at pH 7.5. In the low-Co system (50 μM), reductive transformation of birnessite by Mn(II) aq at pH 7.5 produced Co(II)-substituted feitknechtite, a conversion that was accompanied by reduction of sorbed Co(III) to Co(II) which was partially released to solution. The strong effects of co-sorption are attributed to the similarity in sorption mechanisms of Co(II) and Mn(II), which both sorb as a mixture of di- and trivalent species. Finally, the results of this work demonstrate that aqueous Mn(II) may significantly affect the reactivity of phyllomanganate sorbents towards dissolved Co(II), and therefore impact the speciation and solubility of this trace metal in anoxic and suboxic geochemical environments.