Per F. Peterson

Bio: Per F. Peterson is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Brayton cycle & Fusion power. The author has an hindex of 25, co-authored 186 publications receiving 3645 citations. Previous affiliations of Per F. Peterson include Lawrence Livermore National Laboratory.

Net-zero emissions energy systems

Abstract: Some energy services and industrial processes-such as long-distance freight transport, air travel, highly reliable electricity, and steel and cement manufacturing-are particularly difficult to provide without adding carbon dioxide (CO2) to the atmosphere. Rapidly growing demand for these services, combined with long lead times for technology development and long lifetimes of energy infrastructure, make decarbonization of these services both essential and urgent. We examine barriers and opportunities associated with these difficult-to-decarbonize services and processes, including possible technological solutions and research and development priorities. A range of existing technologies could meet future demands for these services and processes without net addition of CO2 to the atmosphere, but their use may depend on a combination of cost reductions via research and innovation, as well as coordinated deployment and integration of operations across currently discrete energy industries.

Net-zero Emissions Energy Systems

Abstract: Models show that to avert dangerous levels of climate change, global carbon dioxide emissions must fall to zero later this century. Most of these emissions arise from energy use. Davis et al. review what it would take to achieve decarbonization of the energy system. Some parts of the energy system are particularly difficult to decarbonize, including aviation, long-distance transport, steel and cement production, and provision of a reliable electricity supply. Current technologies and pathways show promise, but integration of now-discrete energy sectors and industrial processes is vital to achieve minimal emissions. Net emissions of CO2 by human activities - including not only energy services and industrial production but also land use and agriculture - must approach zero in order to stabilize global mean temperature. Energy services such as light-duty transportation, heating, cooling, and lighting may be relatively straightforward to decarbonize by electrifying and generating electricity from variable renewable energy sources (such as wind and solar) and dispatchable ("on-demand") nonrenewable sources (including nuclear energy and fossil fuels with carbon capture and storage). However, other energy services essential to modern civilization entail emissions that are likely to be more difficult to fully eliminate. These difficult-to-decarbonize energy services include aviation, long-distance transport, and shipping; production of carbon-intensive structural materials such as steel and cement; and provision of a reliable electricity supply that meets varying demand. Moreover, demand for such services and products is projected to increase substantially over this century. The long-lived infrastructure built today, for better or worse, will shape the future. Here, we review the special challenges associated with an energy system that does not add any CO2 to the atmosphere (a net-zero emissions energy system). We discuss prominent technological opportunities and barriers for eliminating and/or managing emissions related to the difficult-to-decarbonize services; pitfalls in which near-term actions may make it more difficult or costly to achieve the net-zero emissions goal; and critical areas for research, development, demonstration, and deployment. It may take decades to research, develop, and deploy these new technologies. DOI Link: https://doi.org/10.1126/science.aas9793

Molten-Salt-Cooled Advanced High-Temperature Reactor for Production of Hydrogen and Electricity

Abstract: The molten-salt-cooled Advanced High-Temperature Reactor (AHTR) is a new reactor concept designed to provide very high-temperature (750 to 1000°C) heat to enable efficient low-cost thermochemical p...

Diffusion Layer Theory for Turbulent Vapor Condensation With Noncondensable Gases

Abstract: In turbulent condensation with noncondensable gas, a thin noncondensable layer accumulated and generates a diffusional resistance to condensation and sensible heat transfer. By expressing the driving potential for mass transfer as a difference in saturation temperatures and using appropriate thermodynamic relationships, here an effective condensation thermal conductivity is derived. With this formulation, experimental results for vertical tubes and plates demonstrate that condensation obeys the heat and mass transfer analogy, when condensation and sensible heat tranfer are considered simultaneously

High-Temperature Liquid-Fluoride-Salt Closed-Brayton-Cycle Solar Power Towers

Abstract: Liquid-fluoride-salt heat transfer fluids are proposed to raise the heat-to-electricity efficiencies of solar power towers to about 50%. The liquid salt would deliver heat from the solar furnace at temperatures between 700°C and 850°C to a closed multireheat Brayton power cycle using nitrogen or helium as the working fluid. During the daytime, hot salt may also be used to heat graphite, which would then be used as a heat storage medium to make night-time operations possible. Graphite is a low-cost high-heat-capacity solid that is chemically compatible with liquid fluoride salts at high temperatures. About half the cost of a solar power tower is associated with the mirrors that focus light on the receiver, and less than one-third is associated with the power cycle and heat storage. Consequently, increasing the efficiency by 20–30% has the potential for major reductions in the cost of electricity. Peak temperatures and efficiencies of current designs of power towers are restricted by (1) the use of liquid nitrate salts that decompose at high temperatures and (2) steam cycles in which corrosion limits peak temperature. The liquid-fluoride-salt technology and closed Brayton power cycles are being developed for high-temperature nuclear reactors. These developments may provide the technology and industrial basis for an advanced solar power tower.

Progress and Perspectives of Electrochemical CO2 Reduction on Copper in Aqueous Electrolyte

Abstract: To date, copper is the only heterogeneous catalyst that has shown a propensity to produce valuable hydrocarbons and alcohols, such as ethylene and ethanol, from electrochemical CO2 reduction (CO2R). There are variety of factors that impact CO2R activity and selectivity, including the catalyst surface structure, morphology, composition, the choice of electrolyte ions and pH, and the electrochemical cell design. Many of these factors are often intertwined, which can complicate catalyst discovery and design efforts. Here we take a broad and historical view of these different aspects and their complex interplay in CO2R catalysis on Cu, with the purpose of providing new insights, critical evaluations, and guidance to the field with regard to research directions and best practices. First, we describe the various experimental probes and complementary theoretical methods that have been used to discern the mechanisms by which products are formed, and next we present our current understanding of the complex reaction networks for CO2R on Cu. We then analyze two key methods that have been used in attempts to alter the activity and selectivity of Cu: nanostructuring and the formation of bimetallic electrodes. Finally, we offer some perspectives on the future outlook for electrochemical CO2R.

Theory and Design of Charged Particle Beams

Abstract: Review of Charged Particle Dynamics. Beam Optics and Focusing Systems Without Space Charge. Linear Beam Optics with Space Charge. Self-Consistent Theory of Beams. Emittance Variation. Beam Physics Research from 1993 to 2007. Appendices. List of Frequently Used Symbols. Bibliography. Index.

Reliability Engineering and System Safety

Abstract: This paper presents a polynomial dimensional decomposition (PDD) method for global sensitivity analysis of stochastic systems subject to independent random input following arbitrary probability distributions. The method involves Fourier-polynomial expansions of lower-variate component functions of a stochastic response by measure-consistent orthonormal polynomial bases, analytical formulae for calculating the global sensitivity indices in terms of the expansion coefficients, and dimension-reduction integration for estimating the expansion coefficients. Due to identical dimensional structures of PDD and analysis-of-variance decomposition, the proposed method facilitates simple and direct calculation of the global sensitivity indices. Numerical results of the global sensitivity indices computed for smooth systems reveal significantly higher convergence rates of the PDD approximation than those from existing methods, including polynomial chaos expansion, random balance design, state-dependent parameter, improved Sobol’s method, and sampling-based methods. However, for non-smooth functions, the convergence properties of the PDD solution deteriorate to a great extent, warranting further improvements. The computational complexity of the PDD method is polynomial, as opposed to exponential, thereby alleviating the curse of dimensionality to some extent. Mathematical modeling of complex systems often requires sensitivity analysis to determine how an output variable of interest is influenced by individual or subsets of input variables. A traditional local sensitivity analysis entails gradients or derivatives, often invoked in design optimization, describing changes in the model response due to the local variation of input. Depending on the model output, obtaining gradients or derivatives, if they exist, can be simple or difficult. In contrast, a global sensitivity analysis (GSA), increasingly becoming mainstream, characterizes how the global variation of input, due to its uncertainty, impacts the overall uncertain behavior of the model. In other words, GSA constitutes the study of how the output uncertainty from a mathematical model is divvied up, qualitatively or quantitatively, to distinct sources of input variation in the model [1].