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The synergies of SMAP enhanced and MODIS products in a random forest regression for estimating 1 km soil moisture over Africa using Google Earth Engine

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Big Earth Data 2024年第1期8卷 33-57页

作者： Farzane Mohseni Amirhossein Ahrari Jan-Henrik Haunert Carsten Montzka Institute of Geodesy and Geoinformation University of BonnBonnGermany Water Energy and Environmental Engineering Research UnitUniversity of OuluOuluFinland Institute of Bio-and Geosciences:Agrosphere(IBG-3) Forschungszentrum Jülich GmbHJülichGermany

Due to the coarse scale of soil moisture products retrieved from passive microwave observations(SMPMW),several downscaling methods have been developed to enable regional scale ***,it can be challenging for users to access final data products and algorithms,as well as managing different data sources and formats,various data processing methods,and the complexity of the workflows from raw data to information ***,the Google Earth Engine(GEE),which as of late offers SMPMW,is used to implement a workflow for retrieving 1 km SM at a depth of 0-5 cm using MODIS optical/thermal measurements,the SM_(PMW)coarse scale product,and a random forest *** proposed method was implemented on the African continent to estimate weekly SM *** results of this study were evaluated against in-situ measurements of three validation ***,in comparison to the original SM_(PMW)product,which was limited by a spatial resolution of only 9 km,this method is able to estimate SM at 1 km spatial resolution with acceptable accuracy(an average correlation coefficient of 0.64 and a ubRMSD of 0.069 m^(3)/m^(3)).The results show that the proposed method in GEE provides a precise estimation of SM with a higher spatial resolution across the entire continent.

关键词： Soil moisture SMAP Google Earth Engine random forest regression MODIS

Opportunities for large language models and discourse in engineering

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Energy and AI 2024年第3期17卷 136-142页

作者： Jan Göpfert Jann M.Weinand Patrick Kuckertz Detlef Stolten Institute of Energy and Climate Research–Techno-economic Systems Analysis(IEK-3) Forschungszentrum Jülich GmbHJülich52425Germany Chair for Fuel Cells RWTH Aachen UniversityFaculty of Mechanical EngineeringAachen52062Germany

In recent years, large language models have achieved breakthroughs on a wide range of benchmarks in natural language processing and continue to increase in performance. Recently, the advances of large language models have raised interest outside the natural language processing community and could have a large impact on daily life. In this paper, we pose the question: How will large language models and other foundation models shape the future product development process? We provide the reader with an overview of the subject by summarizing both recent advances in natural language processing and the use of information technology in the engineering design process. We argue that discourse should be regarded as the core of engineering design processes, and therefore should be represented in a digital artifact. On this basis, we describe how foundation models such as large language models could contribute to the design discourse by automating parts thereof that involve creativity and reasoning, and were previously reserved for humans. We describe how simulations, experiments, topology optimizations, and other process steps can be integrated into a machine-actionable, discourse-centric design process. As an example, we present a design discourse on the optimization of wind turbine blades. Finally, we outline the future research that will be necessary for the implementation of the conceptualized framework.

关键词： Product development process Conceptual design Design methodology Design generation Natural language processing Foundation models Multi-modal models

A novel approach towards parametric assessment of reliability and resilience of high voltage mica-based insulation systems by statistical analysis of experimental failure data

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High Voltage 2024年第2期9卷 495-507页

作者： Shahram Negari Davoud Esmaeil Moghadam Integrated Power Services ClevelandOhioUSA Valeo eAutomotive Germany gmbh ErlangenGermany

Insulation systems in high-voltage electric machines play a pivotal role in the reliable operation and longevity of the ***-based insulation materials have proven to possess and maintain excellent dielectric properties in the long run and prevent premature insulation *** qualifications tests,such as voltage endurance,are outlined in IEC and IEEE *** authors,however,take a different parametric approach,opting for reliability assessment of insulation systems using derived three-parameter Weibull ***,instead of simple pass–fail criteria,empirical data is employed to determine failure rate probabilities quantitatively and *** data,including breakdown,dissipation factor,and partial discharge mea-surements,are used to construct the Weibull distribution model to predict fault and failure rates and calculate hazard *** rigorous examinations interpreted through the analytical model help assess insulation system resilience and particularly the impact of electrical field stress and mica *** of electrical stress from 66.75 to 71.20 V/mil demonstrated how the mean time to failure of the system changed from 146.4 to 85.1 at 3 Un,hence identifying opportunities for design improvement and uncovering performance ***,the developed framework enhances comprehension of insulation system failure probabilities,guiding design decisions and ensuring a secure and reliable operation of electrical machines across applications.

关键词： insulation parametric approach

Explainability and Interpretability in Electric Load Forecasting Using Machine Learning Techniques–A Review

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Energy and AI 2024年第2期16卷 483-496页

作者： Lukas Baur Konstantin Ditschuneit Maximilian Schambach Can Kaymakci Thomas Wollmann Alexander Sauer Fraunhofer Institute for Manufacturing Engineering and Automation IPA Nobelstraße 12Stuttgart70569Germany Institute for Energy Efficiency in Production(EEP) University of StuttgartNobelstraße 12Stuttgart70569Germany Merantix Momentum gmbh Max-Urich-Straße 3Berlin13355Germany

Electric Load Forecasting(ELF)is the central instrument for planning and controlling demand response programs,electricity trading,and consumption *** to the increasing automation of these processes,meaningful and transparent forecasts become more and more ***,at the same time,the complexity of the used machine learning models and architectures *** there is an increasing interest in interpretable and explainable load forecasting methods,this work conducts a literature review to present already applied approaches regarding explainability and interpretability for load forecasts using Machine *** on extensive literature research covering eight publication portals,recurring modeling approaches,trends,and modeling techniques are identified and clustered by properties to achieve more interpretable and explainable load *** results on interpretability show an increase in the use of probabilistic models,methods for time series decomposition and the use of fuzzy logic in addition to classically interpretable *** explainable approaches are Feature Importance and Attention *** discussion shows that a lot of knowledge from the related field of time series forecasting still needs to be adapted to the problems in *** to other applications of explainable and interpretable methods such as clustering,there are currently relatively few research results,but with an increasing trend.

关键词： Electric load forecasting Explainability InterpretabilityStructured review

Deep learning-based prediction of 3-dimensional silver contact shapes enabling improved quality control in solar cell metallization

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Energy and AI 2024年第3期17卷 513-524页

作者： Marius Singler Akshay Patil Linda Ney Andreas Lorenz Sebastian Tepner Florian Clement Fraunhofer Institute for Solar Energy Systems(ISE) Heidenhofstr.279110 FreiburgGermany EKRA Automatisierungstechnik gmbh Zeppelinstraße 1674357 BonnigheimGermany

The industrial metallization of Si solar cells predominantly relies on screen printing,with silver as the preferred electrode ***,the design of commercial screens often leads to suboptimal silver usage and increased electrical resistance due to print-related inhomogeneities like mesh marks,constrictions and ***-time monitoring of quality parameters during production has thus become increasingly *** inline optical quality control systems usually only include 2D visualizations of the printed layout,which limits their effectiveness in quality *** that allow 3D measurements are usually slow,expensive,and therefore not worth considering in most *** research focuses on the development of a model that can estimate the three-dimensional shape of printed contact fingers from a single 2D image without the need of additional hardware using deep ***,a workflow for the generation of training data,which involves the creation of image pairs from a 2D microscope and a 3D confocal laser scanning microscope(CLSM)to accurately represent solar cell fingers,is *** model training,the predicted height maps are compared with the ground truth height maps,and the robustness of the model with respect to a paste variation and screen parameter variation is *** results confirm the feasibility and reliability of deep learning-based 3D shape estimation,extending its applicability to new,previously unseen data from screen-printed contact *** a structural similarity index(SSIM)score of 0.76,a strong correlation between the estimated and ground truth height maps is *** summary,our deep learning-based approach for height map estimation offers an effective and reliable solution for fast inline detection and analysis of the cross-sectional area of the printed contact fingers.

关键词： Deep Learning Front-side metallization Image2Heigth Solar cell Screen-printing

Leveraging machine learning to generate a unified and complete building height dataset for Germany

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Energy and AI 2024年第3期17卷 327-341页

作者： Kristina Dabrock Noah Pflugradt Jann Michael Weinand Detlef Stolten Forschungszentrum Jülich gmbh Institute of Climate and Energy SystemsJülich Systems Analysis52425 JülichGermany RWTH Aachen University Chair for Fuel CellsFaculty of Mechanical Engineering52062 AachenGermany

Building geometry data is crucial for detailed, spatially-explicit analyses of the building stock in energy systems analysis and beyond. Despite the existence of diverse datasets and methods, a standardized and validated approach for creating a nation-wide unified and complete dataset of German building heights is not yet available. This study develops and validates such a methodology, combining different data sources for building footprints and heights and filling gaps in height data using an XGBoost machine learning algorithm. The XGBoost model achieves a mean absolute error of 1.78 m at the national level and between 1.52 m and 3.47 m at the federal state level. The goal is proving the applicability of the methodology at a large scale and creating a useful dataset. The resulting dataset is thoroughly evaluated on a building-by-building level and spatially resolved statistics on the quality of the dataset are reported. This detailed validation found that the building number and footprint area of German building stock is 90.31 % and 94.84 % correct, respectively, and the building height accuracy is 0.59 m at the national level. However, errors are not homogeneous across Germany and further research is needed into the impact of including additional datasets, especially for regions and building types with lower accuracies. This study proves that the chosen methodology is useful for generating a building height dataset and the workflow, with some modifications for regional data availability, can be transferred to other countries. The generated building dataset for Germany constitutes a valuable data basis for the research community in fields such as energy research, urban planning and building decarbonization policy development.

关键词： Machine learning XGBoost Building height Building footprint 3-D building data Geodata Spatial analysis

Development of an ultrathin liquid sheet target for laser ion acceleration at high repetition rates in the kilohertz range

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High Power Laser Science and Engineering 2024年第3期12卷 134-145页

作者： M.Füle A.P.Kovács T.Gilinger M.Karnok P.Gaál S.Figul G.Marowsky K.Osvay National Laser-Initiated Transmutation Laboratory University of SzegedSzegedHungary Department of Experimental Physics University of SzegedSzegedHungary ELI ALPS ELI-HU Non-Profit Ltd.SzegedHungary Department of Optics and Quantum Electronics University of SzegedSzegedHungary Advanced Microfluidic Systems gmbh GöttingenGermany

A colliding microjet liquid sheet target system was developed and tested for pairs of round nozzles of 10,11 and 18μm in *** sheet's position stability was found to be better than a few *** interaction with 50 mJ laser pulses,the 18μm jet has a resonance amplitude of 16μm at a repetition rate of 33 Hz,while towards 100 Hz it converges to 10μm for all nozzles.A white-light interferometric system was developed to measure the liquid sheet thickness in the target chamber both in air and in vacuum,with a measurement range of 182 nm±1μm and an accuracy of±3%.The overall shape and 3D shape of the sheet follow the Hasson±Peck model in *** vacuum versus air,the sheet gradually loses 10%of its thickness,so the thinnest sheet achieved was below 200 nm at a vacuum level of 10±4mbar,and remained stable for several hours of operation.

关键词： diagnostics laser ion acceleration nanometric liquid sheet targets vacuum test

Counting and measuring particles sized from soot to pollen

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China Particuology 2007年第5期5卷 359-361页

作者： Martin Schmidt Sven Schütz Leander Mlter Palas gmbh Greschbachstr. 3b76229 KarlsruheGermany

For number concentration measurements of superfine particles a condensation nucleus counter （CNC） is frequently used. The combination of a new CNC module with a white light aerosol spectrometer and a passive collector makes possible accurate time-resolved determination of particle number within the overall size range of 10 nm to 40 μm and at concentrations up to 10^5 particles/cm^3. With the aerosol spectrometer a high time-resolved particle size determination is also possible in the size range of 0.3-40 μm up to the same high number concentrations of 10^5 particles/cm^3.

关键词： CNC Particles Size

3D U-Net Segmentation Improves Root System Reconstruction from 3D MRI Images in Automated and Manual Virtual Reality Work Flows

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Plant Phenomics 2023年第3期5卷 598-611页

作者： Tobias Selzner Jannis Horn Magdalena Landl Andreas Pohlmeier Dirk Helmrich Katrin Huber Jan Vanderborght Harry Vereecken Sven Behnke Andrea Schnepf Forschungszentrum Juelich gmbh Agrosphere(IBG-3)JuelichGermany Autonomous Intelligence Systems Group University of BonnBonnGermany Forschungszentrum Juelich gmbh Juelich Supercomputing CenterJuelichGermany

Magnetic resonance imaging(MRI)is used to image root systems grown in opaque ***,reconstruction of root system architecture(RSA)from 3-dimensional(3D)MRI images is *** resolution and poor contrast-to-noise ratios(CNRs)hinder automated ***,manual reconstruction is still widely ***,we evaluate a novel 2-step work flow for automated RSA *** the first step,a 3D U-Net segments MRI images into root and soil in *** the second step,an automated tracing algorithm reconstructs the root systems from the segmented *** evaluated the merits of both steps for an MRI dataset of 8 lupine root systems,by comparing the automated reconstructions to manual reconstructions of unaltered and segmented MRI images derived with a novel virtual reality *** found that the U-Net segmentation offers profound benefits in manual reconstruction:reconstruction speed was doubled(+97%)for images with low CNR and increased by 27%for images with high *** root lengths were increased by 20%and 3%,***,we propose to use U-Net segmentation as a principal image preprocessing step in manual work *** root length derived by the tracing algorithm was lower than in both manual reconstruction methods,but segmentation allowed automated processing of otherwise not readily usable MRI ***,model-based functional root traits revealed similar hydraulic behavior of automated and manual *** studies will aim to establish a hybrid work flow that utilizes automated reconstructions as scaffolds that can be manually corrected.

关键词： Root utilize otherwise