Big Data Analytics for Long-Term Meteorological Observations at Hanford Site

A growing number of physical objects with embedded sensors with typically high volume and frequently updated data sets has accentuated the need to develop methodologies to extract useful information from big data for supporting decision making. This study applies a suite of data analytics and core principles of data science to characterize near real-time meteorological data with a focus on extreme weather events. To highlight the applicability of this work and make it more accessible from a risk management perspective, a foundation for a software platform with an intuitive Graphical User Interface (GUI) was developed to access and analyze data from a decommissioned nuclear production complex operated by the U.S. Department of Energy (DOE, Richland, USA). Exploratory data analysis (EDA), involving classical non-parametric statistics, and machine learning (ML) techniques, were used to develop statistical summaries and learn characteristic features of key weather patterns and signatures. The new approach and GUI provide key insights into using big data and ML to assist site operation related to safety management strategies for extreme weather events. Specifically, this work offers a practical guide to analyzing long-term meteorological data and highlights the integration of ML and classical statistics to applied risk and decision science.

Accurate and Rapid Forecasts for Geologic Carbon Storage via Learning-Based Inversion-Free Prediction

Carbon capture and storage (CCS) is one approach being studied by the U.S. Department of Energy to help mitigate global warming. The process involves capturing CO2 emissions from industrial sources and permanently storing them in deep geologic formations (storage reservoirs). However, CCS projects generally target “green field sites,” where there is often little characterization data and therefore large uncertainty about the petrophysical properties and other geologic attributes of the storage reservoir. Consequently, ensemble-based approaches are often used to forecast multiple realizations prior to CO2 injection to visualize a range of potential outcomes. In addition, monitoring data during injection operations are used to update the pre-injection forecasts and thereby improve agreement between forecasted and observed behavior. Thus, a system for generating accurate, timely forecasts of pressure buildup and CO2 movement and distribution within the storage reservoir and for updating those forecasts via monitoring measurements becomes crucial. This study proposes a learning-based prediction method that can accurately and rapidly forecast spatial distribution of CO2 concentration and pressure with uncertainty quantification without relying on traditional inverse modeling. The machine learning techniques include dimension reduction, multivariate data analysis, and Bayesian learning. The outcome is expected to provide CO2 storage site operators with an effective tool for timely and informative decision making based on limited simulation and monitoring data.

Control solar en envolvente vidriada tropical para mejorar el desempeño energético-ambiental por climatización

Con el objetivo de fundamentar la estrategia de control solar como propuesta efectiva en la rehabilitación energética de un edificio de oficinas de los años 50´s, se realiza un diagnóstico del comportamiento de la demanda energética por climatización debido a su fenestración translúcida. Para el estudio se modelan los tipos de espacios más comunes (con una, dos o tres fachadas de vidrio) los cuales son objeto de simulaciones horarias que permiten pronosticar la demanda de energía anual para enfriamiento. Además, se determina el impacto ambiental que provoca este tipo de carpintería en las condiciones tropicales, de alta incidencia solar y de producción de energía de Cuba. Se utiliza Energy Plus, el motor más reconocido y avanzado de Simulación Energética de Edificios, desarrollado por el Departamento de Energía de los EEUU. Fundamentadas en los resultados se realizan y evalúan dos propuestas de diseño de control solar en las fachadas sureste y suroeste, las cuales demuestran su efectividad a partir del ahorro pronóstico anual de energía eléctrica por climatización consecuencia del recurso de sombreado. También se demuestra la influencia de la orientación en el diseño de los elementos componentes de la envolvente vertical para favorecer, con su especificidad local, la eficiencia energética, la identidad; así como la cultura energética convocada por la dirección de la nación. In order to justify the strategy of solar control like effective proposal in the energetic rehabilitation of an office building of the years 50 ´s. This paper present a diagnosis of the behavior of the cooling energetic demand due to its glazed windows. For the study are modeled the types of spaces more common of the building (with one, two or three glass facades) which are simulated each one hour to predict the annual energy demand for cooling. In addition, the environmental impact is determined that causes this window type in the tropical conditions, of high solar incidence and dependence of fuels imported for the energy generation in Cuba. It is used Energy Plus the most advanced motor in Energy Simulation of Buildings, developed by U.S. Department of Energy Building Technologies Office. Based in the results are carried out and evaluate three designs of solar control in the facades southeast and southwest, which demonstrate their effectiveness in the saving annual of electric power for cooling. The results demonstrate the influence of the orientation in the design of the vertical envelope component elements to favor, with their local specificity, the energy efficiency and the identity, as well as the energetic culture convoked by the government of the nation.

Hydrogen Isotopes Permeation in Clean or Unoxidized FeCrAl Alloys: A Review

The US Department of Energy is working with fuel vendors to develop accident tolerant fuels (ATF) for the current fleet of light water reactors (LWRs). The ATF should be more resilient to loss of coolant accident scenarios and help extending the life of the operating LWRs. One of the proposed ATF concepts is to use iron-chromium-aluminum (FeCrAl) alloys for the cladding of the fuel. A concern in using ferritic FeCrAl is that this type of cladding may result in an increase in the concentration of tritium in the coolant. The objective of the current critical review is to collect and assess information from the literature regarding diffusion or permeation of hydrogen (H) and its isotopes deuterium (D) and Tritium (T) across industrial alloys (including FeCrAl) used or intended for the nuclear industry. Over a hundred years of data reviewed shows that the solubility of hydrogen in ferritic alloys is lower than in austenitic alloys but hydrogen permeates faster through a ferritic material than through austenitic materials. The tritium permeation rates in FeCrAl alloys are between those in austenitic stainless steels and in ferritic FeCr steels. The activation energy for hydrogen permeation is approximately 30 pct higher in the austenitic alloys compared with the ferritic (typically ∼ 50 kJ/mol in ferritic vs. ∼ 65 kJ/mol in the austenitic). None of the major elements in FeCrAl alloys react with hydrogen to form detrimental hydride phases. The effect of surface oxides on FeCrAl delaying hydrogen entrance into FeCrAl alloy is not part of this review.

Directed Energy Beam Weapons the Dawn of a New Military Age

Aftermath of “Havana Syndrome” that took place in Cuba, at around 2016 – 2017 time-frame, where American diplomat got mysterious sickness, the dawn of a new military age was born, where directed energy weapons in form waves are now in play. Among concerned government agencies, they still cannot find the source of the sickness except, stating that whatever was the cause, it is unnatural source, but rather man-made weapons in form of high microwave beam weapon. However, this author with this short review is going to show a different perspective of directed energy beam weapons, knowingly that this type weapons are not anything new and scientist and engineer, at national laboratories, department of energy and defense level including some universities nation-wide have been involved with research and development of such direct energy weapons. The battles of tomorrow are not going to take place with speed of bullet or artillery shell, but rather will be fought with speed of light and electron, and that is why the new military age presents itself along with new innovative technologies that is discussed here in this short review. For purpose beam weapons as directed energy we are not taking under consideration, the high power energy laser, since it is beyond the scope of this short review, however we focus on wave frequencies that are falling within high power microwave bandwidth and we introduce another beam weapon’s concept that is known as scalar wave, which we know it as longitudinal scalar wave, that possibly can justify the above sickness caused by the unnatural source, which falls within a man-made source of energy that can travel long distance and penetrated even through Faraday’s cage and any other obstacle in front of very similar to behavior and characteristic of soliton wave. Whatever covert sound or high energy acoustic or wave weapon this man-made phenomena was or is will be discussed in this report with some means of science physics behind it. All scientific discussion in this short review is presentation of this author period

Testing of Heat Transfer Coefficients and Frictional Losses in Internally Ribbed Tubes and Verification of Results through CFD Modelling

This paper presents experimental determination of the heat transfer coefficient and the friction factor in an internally rifled tube. The experiment was carried out on a laboratory stand constructed in the Department of Energy of the Cracow University of Technology. The tested tube is used in a Polish power plant in a supercritical circulating fluidized bed (CFB) boiler with the power capacity of 460 MW. Local heat transfer coefficients were determined for Reynolds numbers included in the range from ~6000 to ~50,000, and for three levels of the heating element power. Using the obtained experimental data, a relation was developed that makes it possible to determine the dimensionless Chilton–Colburn factor. The friction factor was also determined as a function of the Reynolds number ranging from 20,000 to 90,000, and a new correlation was developed that represents the friction factor in internally ribbed tubes. The local heat transfer coefficient and the friction factor obtained during the testing were compared with the CFD modelling results. The modelling was performed using the Ansys Workbench application. The k-ω, the k-ε and the transition SST (Share Stress Transport) turbulence models were applied.

Optimization of the Observing Cadence for the Rubin Observatory Legacy Survey of Space and Time: A Pioneering Process of Community-focused Experimental Design

Vera C. Rubin Observatory is a ground-based astronomical facility under construction, a joint project of the National Science Foundation and the U.S. Department of Energy, designed to conduct a multipurpose 10 yr optical survey of the Southern Hemisphere sky: the Legacy Survey of Space and Time. Significant flexibility in survey strategy remains within the constraints imposed by the core science goals of probing dark energy and dark matter, cataloging the solar system, exploring the transient optical sky, and mapping the Milky Way. The survey’s massive data throughput will be transformational for many other astrophysics domains and Rubin’s data access policy sets the stage for a huge community of potential users. To ensure that the survey science potential is maximized while serving as broad a community as possible, Rubin Observatory has involved the scientific community at large in the process of setting and refining the details of the observing strategy. The motivation, history, and decision-making process of this strategy optimization are detailed in this paper, giving context to the science-driven proposals and recommendations for the survey strategy included in this Focus Issue.

Revisiting matrix-based inversion of scanning mobility particle sizer (SMPS) and humidified tandem differential mobility analyzer (HTDMA) data

Tikhonov regularization is a tool for reducing noise amplification during data inversion. This work introduces RegularizationTools.jl, a general-purpose software package for applying Tikhonov regularization to data. The package implements well-established numerical algorithms and is suitable for systems of up to ~1000 equations. Included is an abstraction to systematically categorize specific inversion configurations and their associated hyperparameters. A generic interface translates arbitrary linear forward models defined by a computer function into the corresponding design matrix. This obviates the need to explicitly write out and discretize the Fredholm integral equation, thus facilitating fast prototyping of new regularization schemes associated with measurement techniques. Example applications include the inversion involving data from scanning mobility particle sizers (SMPSs) and humidified tandem differential mobility analyzers (HTDMAs). Inversion of SMPS size distributions reported in this work builds upon the freely available software DifferentialMobilityAnalyzers.jl. The speed of inversion is improved by a factor of ~200, now requiring between 2 and 5 ms per SMPS scan when using 120 size bins. Previously reported occasional failure to converge to a valid solution is reduced by switching from the L-curve method to generalized cross-validation as the metric to search for the optimal regularization parameter. Higher-order inversions resulting in smooth, denoised reconstructions of size distributions are now included in DifferentialMobilityAnalyzers.jl. This work also demonstrates that an SMPS-style matrixbased inversion can be applied to find the growth factor frequency distribution from raw HTDMA data while also accounting for multiply charged particles. The outcome of the aerosol-related inversion methods is showcased by inverting multi-week SMPS and HTDMA datasets from ground-based observations, including SMPS data obtained at Bodega Marine Laboratory during the CalWater 2/ACAPEX campaign and co-located SMPS and HTDMA data collected at the US Department of Energy observatory located at the Southern Great Plains site in Oklahoma, USA. Results show that the proposed approaches are suitable for unsupervised, nonparametric inversion of large-scale datasets as well as inversion in real time during data acquisition on low-cost reducedinstruction- set architectures used in single-board computers. The included software implementation of Tikhonov regularization is freely available, general, and domain-independent and thus can be applied to many other inverse problems arising in atmospheric measurement techniques and beyond.

Levulinic Acid Production from Macroalgae: Production and Promising Potential in Industry

The development of macroalgal biorefinery products as an alternative source of renewable fuels is an opportunity to solve the dependence on fossil fuels. Macroalgae is a potential biomass that can be developed as a raw material for producing platform chemicals such as levulinic acid (LA). In the industrial sector, LA is among the top 12 biomass-derived feedstocks designated by the U.S. Department of Energy as a high-value chemical. Several studies have been conducted on the production of LA from terrestrial-based biomass, however, there is still limited information on its production from macroalgae. The advantages of macroalgae over terrestrial and other biomasses include high carbohydrate and biomass production, less cultivation cost, and low lignin content. Therefore, this study aims to investigate the potential and challenge of producing LA from macroalgae in the industrial sector and determine its advantages and disadvantages compared with terrestrial biomass in LA production. In this study, various literature sources were examined using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) method to identify, screen, and analyze the data of the published paper. Despite its advantages, there are some challenges in making the production of levulinic acid from macroalgae feasible for development at the industrial scale. Some challenges such as sustainability of macroalgae, the efficiency of pretreatment, and hydrolysis technology are often encountered during the production of levulinic acid from macroalgae on an industrial scale.