炭素価格付け政策と容量メカニズムの相互作用の探究

京都大学新制・課程博士博士(エネルギー科学)甲第24923号エネ博第465号京都大学大学院エネルギー科学研究科エネルギー社会・環境科学専攻(主査)教授 MCLELLAN Benjamin, 教授 下田 宏, 教授 宇根﨑 博信学位規則第4条第1項該当Doctor of Energy ScienceKyoto UniversityDFA

Will Capacity Mechanisms Conflict with Carbon Pricing?

Climate change and related national mitigation targets make the decarbonization of the power sector an urgent need. The power sector faces the challenge of considering the design and interaction between emission reduction policies, which can sometimes counteract each other. This study proposes a framework that can be used to quantitatively study the qualitative link between carbon pricing and capacity pricing. The framework is validated through a case study in Hokkaido, Japan, and used to further investigate the interaction between the two policies through a System Dynamics simulation model and scenario design. The results indicate that a carbon price would promote the introduction of wind power, as well as the reduction in fossil fuels, while the capacity price will mitigate the boom-and-bust investment cycle and stabilize electricity prices. However, when the two policy-based prices act on the power system simultaneously, the advantages will be offset by each other. The existence of the capacity price partially offsets the emission reduction effect of the carbon price, and the carbon price with a lower floor will also indirectly squeeze the generation space of flexible power plants. In order to address these inefficiencies, this study proposed a capacity price focused on subsidizing flexible power plants and also coupled with a higher floor carbon price, which results in a consistent incentive. It also promotes the decommissioning of carbon-intensive base-load power plants and reduces CO₂ emissions significantly

Microwave Enhanced Combustion on a Constant Volume Combustion Chamber for Lean Combustion and EGR Dilution

The effect of microwave enhancement on combustion was investigated using a spherical, constant-volume combustion chamber. Microwave energy at 2.45 GHz was coupled into the spherical chamber using a quarter-wavelength dipole antenna. Standing waves of high-strength electrical fields were created to enhance the flames ignited by a spark plug. Pressure traces of combustion with and without microwaves were recorded to compare the combustion improvements. Microwave power levels and discharge durations were also varied to understand their impact on the level of improvement. Results indicated that the microwave system can effectively accelerate combustion and improve cycle stability for dilute combustion, including lean burn at about 0.8 equivalence ratio and stoichiometric operation with 20% exhaust gas recirculation (EGR) dilution

GenPhys: From Physical Processes to Generative Models

Since diffusion models (DM) and the more recent Poisson flow generative models (PFGM) are inspired by physical processes, it is reasonable to ask: Can physical processes offer additional new generative models? We show that the answer is yes. We introduce a general family, Generative Models from Physical Processes (GenPhys), where we translate partial differential equations (PDEs) describing physical processes to generative models. We show that generative models can be constructed from s-generative PDEs (s for smooth). GenPhys subsume the two existing generative models (DM and PFGM) and even give rise to new families of generative models, e.g., "Yukawa Generative Models" inspired from weak interactions. On the other hand, some physical processes by default do not belong to the GenPhys family, e.g., the wave equation and the Schr\"{o}dinger equation, but could be made into the GenPhys family with some modifications. Our goal with GenPhys is to explore and expand the design space of generative models

Learning Neural Acoustic Fields

Our environment is filled with rich and dynamic acoustic information. When we walk into a cathedral, the reverberations as much as appearance inform us of the sanctuary's wide open space. Similarly, as an object moves around us, we expect the sound emitted to also exhibit this movement. While recent advances in learned implicit functions have led to increasingly higher quality representations of the visual world, there have not been commensurate advances in learning spatial auditory representations. To address this gap, we introduce Neural Acoustic Fields (NAFs), an implicit representation that captures how sounds propagate in a physical scene. By modeling acoustic propagation in a scene as a linear time-invariant system, NAFs learn to continuously map all emitter and listener location pairs to a neural impulse response function that can then be applied to arbitrary sounds. We demonstrate that the continuous nature of NAFs enables us to render spatial acoustics for a listener at an arbitrary location, and can predict sound propagation at novel locations. We further show that the representation learned by NAFs can help improve visual learning with sparse views. Finally, we show that a representation informative of scene structure emerges during the learning of NAFs.Comment: Project page: https://www.andrew.cmu.edu/user/afluo/Neural_Acoustic_Fields

Regulation Mechanism of Processed Cheese Stretchability

In this work, the regulation mechanism of processed cheese stretchability was studied by adjusting the amount of added emulsifying salt (0.6%–3.0%) and potato acetate starch (0.125%–2%) and pH (5.4–5.8). The results showed that as the emulsifying salt increased from 0.6% to 3.0%, the content of bound calcium in processed cheese decreased from (4.42 ± 0.05) to (0.02 ± 0.04) g/kg, the average fat globule size D(4,3) decreased from (73.08 ± 3.16) to (27.90 ± 2.55) μm, and the bound water content increased from (9.57 ± 0.25)% to (10.40 ± 0.25)%, indicating that the calcium crosslinking effect gradually decreased, the emulsifying effect and hydration degree increased, the interaction between protein molecules changed from strong to weak, so the stretchability of processed cheese initially increased and then decreased. As pH increased from 5.4 to 5.8, the content of bound calcium increased from (2.01 ± 0.08) to (2.74 ± 0.05) g/kg, and the average fat globule size D(4,3) decreased from (36.36 ± 2.68) to (21.37 ± 2.39) μm. Fourier transform infrared spectroscopy showed that the bending vibration absorption peaks of O–H and N–H moved to lower wavenumbers, and the bound water content increased from (9.85 ± 0.16)% to (10.74 ± 0.12)%, indicating that the calcium crosslinking effect, emulsifying effect and hydration degree increased, the interaction between protein molecules changed from strong to weak, so the stretchability of processed cheese increased first and then decreased. As potato acetate starch concentration increased from 0.125% to 2%, the average fat globule size D(4,3) decreased from (54.17 ± 2.74) to (29.92 ± 2.71) μm, and the bound water content increased from (9.90 ± 0.38)% to (11.00 ± 0.21)%, indicating that the emulsifying effect and hydration degree increased, and the stretchability increased first and then decreased. At a potato acetate starch concentration of 2%, starch and protein were separated, so the stretchability became worse. In conclusion, the stretchability of processed cheese is comprehensively regulated by the degree of calcium ion chelation, emulsifying effect, electrostatic interaction between protein molecules, water distribution state and protein-polysaccharide phase behavior

Improved prediction of radiation pneumonitis by combining biological and radiobiological parameters using a data-driven Bayesian network analysis

Grade 2 and higher radiation pneumonitis (RP2) is a potentially fatal toxicity that limits efficacy of radiation therapy (RT). We wished to identify a combined biomarker signature of circulating miRNAs and cytokines which, along with radiobiological and clinical parameters, may better predict a targetable RP2 pathway. In a prospective clinical trial of response-adapted RT for patients (n = 39) with locally advanced non-small cell lung cancer, we analyzed patients\u27 plasma, collected pre- and during RT, for microRNAs (miRNAs) and cytokines using array and multiplex enzyme linked immunosorbent assay (ELISA), respectively. Interactions between candidate biomarkers, radiobiological, and clinical parameters were analyzed using data-driven Bayesian network (DD-BN) analysis. We identified alterations in specific miRNAs (miR-532, -99b and -495, let-7c, -451 and -139-3p) correlating with lung toxicity. High levels of soluble tumor necrosis factor alpha receptor 1 (sTNFR1) were detected in a majority of lung cancer patients. However, among RP patients, within 2 weeks of RT initiation, we noted a trend of temporary decline in sTNFR1 (a physiological scavenger of TNFα) and ADAM17 (a shedding protease that cleaves both membrane-bound TNFα and TNFR1) levels. Cytokine signature identified activation of inflammatory pathway. Using DD-BN we combined miRNA and cytokine data along with generalized equivalent uniform dose (gEUD) to identify pathways with better accuracy of predicting RP2 as compared to either miRNA or cytokines alone. This signature suggests that activation of the TNFα-NFκB inflammatory pathway plays a key role in RP which could be specifically ameliorated by etanercept rather than current therapy of non-specific leukotoxic corticosteroids

Portable nuclear magnetic resonance biosensor and assay for a highly sensitive and rapid detection of foodborne bacteria in complex matrices

Abstract Background Nuclear magnetic resonance (NMR) technique is a powerful analytical tool in determining the presence of bacterial contaminants in complex biological samples. In this paper, a portable NMR-based (pNMR) biosensor and assay to detect the foodborne bacteria Escherichia coli O157:H7 is reported. It uses antibody-functionalized polymer-coated magnetic nanoparticles as proximity biomarker of the bacteria which accelerates NMR resonance signal decay. Results The pNMR biosensor operates at 0.47 Tesla of magnetic strength and consists of a high-power pulsed RF transmitter and an ultra-low noise sensing circuitry capable of detecting weak NMR signal at 0.1 μV. The pNMR biosensor assay and sensing mechanism is used in detecting E. coli O157:H7 bacteria in drinking water and milk samples. Experimental results demonstrate that by adding a filtration step in the assay, the pNMR biosensor is able to detect E. coli O157:H7 as low as 76 CFU/mL in water samples and as low as 92 CFU/mL in milk samples in about one min. Conclusion The pNMR biosensor assay and sensing system is innovative for foodborne bacterial detection in food matrices. The lowest detection level for E. coli O157:H7 in water and milk samples is essentially 101 CFU/mL. Although the linear range of detection is only from 101 to 104 CFU/mL, the wider detection range spans from 101 CFU/mL to 107 CFU/mL. Existing pNMR biosensors have detection limits at 103-104 CFU/mL only. The detection technique can be extended to other microbial or viral organisms by merely changing the specificity of the antibodies. Besides food safety, the pNMR biosensor described in this paper has potential to be applied as a rapid detection device in biodefense and healthcare diagnostic applications

Modeling and control of electrical breakdown process of carbon nanotubes

Carbon nanotubes (CNTs) have been found as the promising semiconducting material for the future high performance nanoelectronics. As an important property for applications of a semiconductor, the band gap of a multi-walled CNT is related to its diameter. The capability of adjusting the material band gap is extremely important in sensor and electronics manufacturing. This paper discusses a real-time control method for the selective carbon shell breakdown process to tailor the CNTs band structure. The control method is designed based on the quantum state space model that describes the electron transport in the CNT. The state space anomaly during breakdown process can be observed using robust fault diagnosis technique by combining analytical approach and heuristic approach. The experimental results reported in this paper verify the theoretical findings. As a result, a MWCNT can be converted into a semiconducting material with pre-determined band gap. Copyright © 2007 International Federation of Automatic Control All Rights Reserved.Link_to_subscribed_fulltex