An Integrated physics-based approach to demonstrate the potential of the Landsat Data Continuity Mission (LDCM) for monitoring coastal/inland waters

Monitoring coastal or inland waters, recognized as case II waters, using the existing Landsat technology is somewhat restricted because of its low Signal-to-Noise ratio (SNR) as well as its relatively poor radiometric resolution. As a primary task, we introduce a novel technique, which integrates the Landsat-7 data as a surrogate for LDCM with a 3D hydrodynamic model to monitor the dynamics of coastal waters near river discharges as well as in a small lake environment. The proposed approach leverages both the thermal and the reflective Landsat-7 imagery to calibrate the model and to retrieve the concentrations of optically active components of the water. To do so, the model is first calibrated by optimizing its thermal outputs with the surface temperature maps derived from the Landsat-7 data. The constituent retrieval is conducted in the second phase where multiple simulated concentration maps are provided to an in-water radiative transfer code (Hydrolight) to generate modeled surface reflectance maps. Prior to any remote sensing task, one has to ensure that a dataset comes from a well-calibrated imaging system. Although the calibration status of Landsat-7 has been regularly monitored over multiple desert sites, it was desired to evaluate its performance over dark waters relative to a well-calibrated instrument designed specifically for water studies. In the light of this, several Landsat- 7 images were cross-calibrated against the Terra-MODIS data over deep, dark waters whose optical properties remain relatively stable. This study is intended to lay the groundwork and provide a reference point for similar studies planned for the new Landsat. In an independent case study, the potential of the new Landsat sensor was examined using an EO-1 dataset and applying a spectral optimization approach over case II waters. The water constituent maps generated from the EO-1 imagery were compared against those derived from Landsat-7 to fully analyze the improvement levels pertaining to the new Landsat\u27s enhanced features in a water constituent retrieval framework

A multiphysics approach for modeling gas exchange in microperforated films for modified atmosphere packaging of respiring products

The objective of this work is to quantify, model and verify how the interactions between the respiring products and the surrounding atmosphere in a package affect the gas exchange through a microperforation. The pressure drop generated in a closed system by the metabolic activity of five different products has been determined by direct and indirect measurements. In this way, the estimated compensating hydrodynamic flows that can pass through the microperforated film ranged from 0.34 to 4.75 mL h(-1). A 3D model that considers the mass transfer coupled with the momentum transfer has been proposed to predict the gas concentration profiles around the microperforations originated by the diffusive and convective flows. A novel gas exchange measurement system, able to deliver small convective airflows comparable to those obtained for the different products and conditions, was assembled for the model verification. The model correctly predicts experimental data obtained for different convective flows

Mass & secondary structure propensity of amino acids explain their mutability and evolutionary replacements

Why is an amino acid replacement in a protein accepted during evolution? The answer given by bioinformatics relies on the frequency of change of each amino acid by another one and the propensity of each to remain unchanged. We propose that these replacement rules are recoverable from the secondary structural trends of amino acids. A distance measure between high-resolution Ramachandran distributions reveals that structurally similar residues coincide with those found in substitution matrices such as BLOSUM: Asn Asp, Phe Tyr, Lys Arg, Gln Glu, Ile Val, Met → Leu; with Ala, Cys, His, Gly, Ser, Pro, and Thr, as structurally idiosyncratic residues. We also found a high average correlation (\overline{R} R = 0.85) between thirty amino acid mutability scales and the mutational inertia (I X ), which measures the energetic cost weighted by the number of observations at the most probable amino acid conformation. These results indicate that amino acid substitutions follow two optimally-efficient principles: (a) amino acids interchangeability privileges their secondary structural similarity, and (b) the amino acid mutability depends directly on its biosynthetic energy cost, and inversely with its frequency. These two principles are the underlying rules governing the observed amino acid substitutions. © 2017 The Author(s)

CHARMM: The biomolecular simulation program

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estimators, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numerous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983. © 2009 Wiley Periodicals, Inc.J Comput Chem, 2009.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63074/1/21287_ftp.pd

A scalable parallel framework for analyzing terascale molecular dynamics simulation trajectories

Abstract—As parallel algorithms and architectures drive the longest molecular dynamics (MD) simulations towards the millisecond scale, traditional sequential post-simulation data analysis methods are becoming increasingly untenable. Inspired by the programming interface of Google’s MapReduce, we have built a new parallel analysis framework called HiMach, which allows users to write trajectory analysis programs sequentially, and carries out the parallel execution of the programs automatically. We introduce (1) a new MD trajectory data analysis model that is amenable to parallel processing, (2) a new interface for defining trajectories to be analyzed, (3) a novel method to make use of an existing sequential analysis tool called VMD, and (4) an extension to the original MapReduce model to support multiple rounds of analysis. Performance evaluations on up to 512 cores demonstrate the efficiency and scalability of the HiMach framework on a Linux cluster. I

Development of Integrated Models for Thermal Management in Hybrid Vehicles

[ES] En los últimos años, la industria de la automoción ha hecho un gran esfuerzo para producir sistemas de propulsión más eficientes y menos contaminantes sin menguar su rendimiento. Las nuevas regulaciones impuestas por las autoridades han empujado a la industria hacia la electrificación de los sistemas de propulsión mientras que las tecnologías desarrolladas para el sistema de propulsión convencional, basado en motores de combustión interna alternativos (MCIA), ya no son suficientes. El modelado numérico ha demostrado ser una herramienta indispensable para el diseño, desarrollo y optimización de sistemas de gestión térmica en trenes motrices electrificados, ahorrando costes y reduciendo el tiempo de desarrollo. La gestión térmica en los MCIA siempre ha sido importante para mejorar el consumo, las emisiones y la seguridad. Sin embargo, es todavía más importante en los sistemas de propulsión híbridos, a causa de la complejidad del sistema y al funcionamiento intermitente del MCIA. Además, los trenes motrices electrificados tienen varias fuentes de calor (es decir, MCIA, batería, máquina eléctrica) con diferentes requisitos de funcionamiento térmico. El objetivo principal de este trabajo ha sido desarrollar modelos térmicos para estudiar la mejora de los sistemas de gestión térmica en sistemas de propulsión electrificados (es decir, vehículo híbrido), estudiando y cuantificando la influencia de diferentes estrategias en el rendimiento, la seguridad y la eficiencia de los vehículos. La metodología desarrollada en este trabajo consistió tanto en la realización de experimentos como en el desarrollo de modelos numéricos. De hecho, se llevó a cabo una extensa campaña experimental para validar los diferentes modelos del tren motriz electrificado. Los datos obtenidos de las campañas experimentales sirvieron para calibrar y validar los modelos así como para corroborar los resultados obtenidos por los estudios numéricos. En primer lugar, se estudiaron las diferentes estrategias de gestión térmica de manera independiente para cada componente del tren motriz. Para el MCIA se estudió el uso de nanofluidos, el aislamiento del colector y puertos de escape, así como el cambio de volumen de sus circuitos hidráulicos. De igual forma, se evaluó el impacto de diferentes estrategias para la mejora térmica de las baterías. Además, el modelo de máquina eléctrica se utilizó para desarrollar pruebas experimentales que emulaban el daño térmico producido en ciclos reales de conducción. En segundo lugar, los modelos de tren motriz se integraron utilizando un estándar de co-simulación para evaluar el impacto de un sistema de gestión térmica integrado. Finalmente, se implementó un nuevo control del sistema de gestión de energía para evaluar el impacto de considerar el estado térmico del MCIA al momento de decidir la distribución de potencia del vehículo híbrido. Los resultados han demostrado que el uso de nanofluidos tiene un impacto muy limitado tanto en el MCIA como en el comportamiento térmico de la batería. Además, también mostraron que al reducir el volumen de refrigerante en un 45 %, la reducción en el tiempo de calentamiento del MCIA y el consumo de combustible en comparación con el caso baso fue del 7 % y del 0.4 %, respectivamente. Además, para condiciones de frio (7ºC), el impacto fue todavía mayor, obteniendo una reducción del tiempo de calentamiento y del consumo de combustible del 13 % y del 0.5 % respectivamente. Por otro lado, los resultados concluyeron que durante el calentamiento del MCIA, el sistema integrado de gestión térmica mejoró el consumo de energía en un 1.74 % y un 3 % para condiciones de calor (20ºC) y frío (-20ºC), respectivamente. Esto se debe al hecho que el sistema de gestión térmica integrado permite evitar la caída de temperatura del MCIA cuando el sistema de propulsión está en manera eléctrica pura.[CA] En els últims anys, la indústria de l'automoció ha fet un gran esforç per a produir sistemes de propulsió més eficients i menys contaminants sense minvar el seu rendiment. Les noves regulacions imposades per les autoritats han espentat a la indústria cap a l'electrificació dels sistemes de propulsió mentre que les tecnologies desenvolupades per al sistema de propulsió convencional, basat en motors de combustió interna alternatius (MCIA), ja no són suficients. El modelatge numèric ha demostrat ser una eina indispensable per al disseny, desenvolupament i optimització de sistemes de gestió tèrmica en trens motrius electrificats, estalviant costos i reduint el temps de desenvolupament. La gestió tèrmica en els MCIA sempre ha sigut important per a millorar el consum, les emissions i la seguretat. No obstant això, és encara més important en els sistemes de propulsió híbrids, a causa de la complexitat del sistema i al funcionament intermitent del MCIA. A més, els trens motrius electrificats tenen diverses fonts de calor (és a dir, MCIA, bateria, màquina elèctrica) amb diferents requisits de funcionament tèrmic. L'objectiu principal d'aquest treball va ser desenvolupar models tèrmics per a estudiar la millora dels sistemes de gestió tèrmica en sistemes de propulsió electrificats (és a dir, vehicle híbrid), estudiant i quantificant la influència de diferents estratègies en el rendiment, la seguretat i l'eficiència dels vehicles. La metodologia desenvolupada en aquest treball va consistir tant en la realització d'experiments com en el desenvolupament de models numèrics. De fet, es va dur a terme una extensa campanya experimental per a validar els diferents models del tren motriu electrificat. Les dades obtingudes de les campanyes experimentals van servir per a calibrar i validar els models així com per a corroborar els resultats obtinguts pels estudis numèrics. En primer lloc, es van estudiar les diferents estratègies de gestió tèrmica de manera independent per a cada component del tren motriu. Per al MCIA es va estudiar l'us de nanofluids, l'aïllament del col·lector i ports d'eixida així com el canvi de volum dels seus circuits hidràulics. D'igual forma, es va avaluar l'impacte de diferents estratègies per a la millora tèrmica de les bateries. A més, el model de màquina elèctrica es va utilitzar per a desenvolupar proves experimentals que emulaven el mal tèrmic produït en cicles reals de conducció. En segon lloc, els models de tren motriu es van integrar utilitzant un estàndard de co-simulació per a avaluar l'impacte d'un sistema de gestió tèrmica integrat. Finalment, es va implementar un nou control del sistema de gestió d'energia per a avaluar l'impacte de considerar l'estat tèrmic del MCIA al moment de decidir la distribució de potència del vehicle híbrid. Els resultats han demostrat que l'us de nanofluids té un impacte molt limitat tant en el MCIA com en el comportament tèrmic de la bateria. A més, també van mostrar que en reduir el volum de refrigerant en un 45 %, la reducció en el temps de calfament del MCIA i el consum de combustible en comparació amb el cas base va ser del 7 % i del 0.4 %, respectivament. A més, per a condicions de fred (-7ºC), l'impacte va ser encara major, obtenint una reducció del temps de calfament i del consum de combustible del 13 % i del 0.5 % respectivament. D'altra banda, els resultats van concloure que durant el calfament del MCIA, el sistema integrat de gestió tèrmica va millorar el consum d'energia en un 1.74 % i un 3 % per a condicions de calor (20ºC) i fred (-20ºC), respectivament. Això es deu al fet que el sistema de gestió tèrmica integrat permet evitar la caiguda de temperatura del MCIA quan el sistema de propulsió està en manera elèctrica pura.[EN] In recent years, the automotive industry has made a great effort to produce more efficient and less polluting propulsion systems without diminishing their performance. The new regulations imposed by the authorities have pushed the industry towards the electrification of powertrains while, technologies developed for the conventional propulsion system based on alternative internal combustion engines (ICEs), are no longer sufficient. Numerical modeling has proven to be an indispensable tool for the design, development and optimization of thermal management systems in electrified powertrains, saving costs and reducing development time. Thermal management in ICEs has always been important for improving consumption, emissions and safety. However, it is even more important in hybrid powertrains, due to the complexity of the system and the intermittent operation of the ICE. In addition, electrified powertrains have various heat sources (i.e., ICE, battery, Electric machine) with different thermal operating requirements. The main objective of this work was to develop thermal models to study the improvement of thermal management systems in electrified powertrains (i.e., hybrid electric vehicle), shedding light and quantifying the influence of different strategies on performance, safety and efficiency of the vehicles. The methodology developed in this paper consisted both in carrying out experiments and in developing numerical models. In fact, an extensive experimental campaign was carried out to validate the various models of the electrified powertrain. The data obtained from the experimental campaigns served to calibrate and validate the models as well as to corroborate the results obtained by the numerical studies. Firstly, the different thermal management strategies were studied independently for each component of the powertrain. For the ICE, the use of nanofluids, insulation of exhaust manifold and ports as well as the volume change of its hydraulic circuits were studied. Similarly, the impact of different strategies for the thermal improvement of batteries was evaluated. Furthermore, the electric machine model was used for developing experimental tests which emulated the thermal damage produced in real driving cycles. Secondly, the powertrain models were integrated using a co-simulation standard to assess the impact of an integrated thermal management system. Finally, a new control energy management system was implemented to assess the impact of considering the ICE thermal state when deciding the power split of the hybrid vehicle. The results have shown that the use of nanofluids has a very limited impact on both the ICE and the battery's thermal behaviour. In addition, they also showed that by reducing the volume of coolant by 45 %, the reduction in ICE warm up time and fuel consumption compared to the base case were 7 % and 0.4 %, respectively. In addition, for cold conditions (-7ºC), the impact was even greater, obtaining a reduction in warm up time and fuel consumption of 13 % and 0.5 % respectively. On the other hand, the results concluded that during the warming of ICE, the integrated thermal management system improved energy consumption by 1.74 % and 3 % for warm (20ºC) and cold (-20ºC) conditions, respectively. This is because the integrated TMS makes it possible to prevent the ICE temperature drop when the powertrain is in pure electric mode. Finally, significant gains during Worldwide harmonized Light vehicles Test Cycles (WLTC) and Real Driving Emissions (RDE) cycles were observed when the ICE thermal state was chosen when deciding the power distribution.The author would like to sincerely acknowledge the founding support pro- vided by Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital in the framework of the Ayuda Predoctoral GVA. (ACIF/2020/234). Additionally the author would also acknowledge the support provided by Renault S.A.S.Dreif Bennany, A. (2023). Development of Integrated Models for Thermal Management in Hybrid Vehicles [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/19406

Numerical modelling of electrodeposition process for printed circuit boards manufacturing

Printed circuit boards (PCBs) are used extensively in electronic products to connect assembled components within a system. The so-called vertical interconnect access (via) is a vertical hole or cavity in the PCB filled with metal to facilitate conductivity. The current trend, particularly for high technology products (e.g., 3D packaging), is to manufacture PCBs with high aspect ratio (AR) vias. Typically, the size of such a via is at the micrometer scale (this is why they are termed micro-vias). The most widely used technique for manufacturing micro-vias is electrodeposition of metal (e.g., copper), where the PCB is immersed into a plating cell filled with an electrolyte solution. Using standard conditions, electrodeposition usually does not produce micro-vias with the required quality. This is due to a lack of copper ion transport into the via. This has lead to studies of various ways of enhancing the ion transport. This thesis documents the results from a modelling study into the electrodeposition processes for fabricating high aspect ratio micro-vias. This includes basic electrodeposition and techniques that enhance ion transport such as forced convection (using a pump) and acoustic streaming (using transducers). In this work, a novel numerical method for explicitly tracking the interface between the deposited metal and the electrolyte is implemented and validated under the conditions of basic electrodeposition using experimental data. Results from a parametric study have established a set of design rules for micro-vias fabrication. When ion transport is enhanced by forced convection (e.g., pumping) in the plating cell, we apply a multi-scale modelling methodology that provides interaction between models at the macro level (the plating cell) and the micro level (the interior of a via). Numerical simulations can then be used to verify how ion transport into the micro-via is improved. These results can then be used to identify process conditions for the plating cell which will result in the required flow behaviour at the micro-via. Megasonic agitation can also be used to enhance electrolyte convection in the plating cell. This is achieved by placing megasonic transducers into the plating cell. This leads to several phenomena, one of which is known as the acoustic streaming. Models have been developed for predicting megasonic agitation both at the macro and micro-scales, and a number of designs have been investigated for both open and blind micro-vias

Rainfall Thresholds and Other Approaches for Landslide Prediction and Early Warning

Landslides are destructive processes causing casualties and damage worldwide. The majority of the landslides are triggered by intense and/or prolonged rainfall. Therefore, the prediction of the occurrence of rainfall-induced landslides is an important scientific and social issue. To mitigate the risk posed by rainfall-induced landslides, landslide early warning systems (LEWS) can be built and applied at different scales as effective non-structural mitigation measures. Usually, the core of a LEWS is constituted of a mathematical model that predicts landslide occurrence in the monitored areas. In recent decades, rainfall thresholds have become a widespread and well established technique for the prediction of rainfall-induced landslides, and for the setting up of prototype or operational LEWS. A rainfall threshold expresses, with a mathematic law, the rainfall amount that, when reached or exceeded, is likely to trigger one or more landslides. Rainfall thresholds can be defined with relatively few parameters and are very straightforward to operate, because their application within LEWS is usually based only on the comparison of monitored and/or forecasted rainfall. This Special Issue collects contributions on the recent research advances or well-documented applications of rainfall thresholds, as well as other innovative methods for landslide prediction and early warning. Contributions regarding the description of a LEWS or single components of LEWS (e.g., monitoring approaches, forecasting models, communication strategies, and emergency management) are also welcome

Multidisciplinary Optimization of Hybrid Electric Vehicles: Component Sizing and Power Management Logic

A survey of the existing literature indicates that optimization on the power management logic of hybrid electric vehicle is mostly performed after the design of the powertrain architecture or the power source components are finalized. The goal of this research is to utilize Multidisciplinary Design Optimization (MDO) to automate and optimize the vehicle’s powertrain component sizes, while simultaneously determining the optimal power management logic in developing the most cost-effective system solution. A generic, modular, and flexible vehicle model utilizing a backward-looking architecture is created using scalable powertrain components. The objective of the research work is to study the energy efficiency of the vehicle system, where the dynamics of the vehicle is not of concern; a backward-looking architecture could be used to compute the power consumption and the overall efficiency accurately while minimizing the required computing resource. An optimization software platform utilizing multidisciplinary design optimization approach is implemented containing the generic vehicle model and an optimizer of the user’s choice. The software model is created in the MATLAB/Simulink environment, where the optimization code and the powertrain component properties are implemented using m-files, and the power consumption calculations of the vehicle system are performed in Simulink. Furthermore, a feature-based optimization technique is developed with the motivation of significantly reducing the simulation run-time. To demonstrate the capabilities of the developed approach and contributions of the research, two optimization case studies are undertaken: (i) series hybrid electric vehicles, and (ii) police vehicle anti-idling system. As the first case study, a plug-in battery-only series hybrid electric vehicle with similar power components as the Chevrolet Volt is created, where the battery size and the power management logic are simultaneously optimized. The objective function of the optimizer is defined from the financial cost perspective, where the objective is to minimize the initial cost of batteries, gasoline and electricity consumption over a period of five years, and the carbon tax as a penalty function for fuel emissions. The battery-only series hybrid electric vehicle is subsequently extended to include ultracapacitors, and the optimization process is expanded to the rest of the powertrain components and power management logic. A comparison between the optimization algorithms found that only genetic algorithm (GA) was capable of finding the optimal solution during a full simulation, while simulated annealing and pattern search were not able to converge to any solution after a 24-hour period. A comparison between the full genetic algorithm optimization and the feature-based (FB) method with secondary optimization found that although the final cost function of the FB methodology is higher than that of the full GA optimization, the total simulation run-time is approximately ten times less using the FB method. The behaviour of the solutions found via both methods exhibited almost identical characteristics, further confirming the validity of the feature-based methodology. Finally, a benchmarking comparison found that with more accurate manufacturers’ component data and additional appropriate performance requirements, the proposed software platform will be capable of predicting a solution that is comparable to the Chevrolet Volt. The second case study involves optimizing an anti-idling system for police vehicles using the same optimization algorithm and generic vehicle model. The goal of the optimization study is to select an additional battery and determine the power management logic to reduce the engine idling time of a police vehicle. It is found that depending on the SOC threshold, the duration of time over which the engine is activated varies in a non-linear fashion, where local minima and maxima exist. A design study confirmed that by utilizing the anti-idling system, significant cost reduction can be realized when compared to one without the anti-idling system. A comparison between the various optimization algorithms showed that the feature-based optimization can obtain a relatively accurate solution while reducing simulation time by approximately 90%. This significant reduction in simulation time warrants the feature-based optimization technique a powerful tool for vehicle design. Due to the high cost of the electrical energy storage components, it is currently still more cost-effective to use the fossil fuel as the primary energy source for transportation. However, given the rise of fuel cost and the advancement in the electrical energy storage technology, it is inevitable that the cost of the electrical and chemical energy storage method will reach a balance point. The proposed optimization platform allows the user the capability and flexibility to obtain the optimal vehicle solution with ease at any given time in the future