The main objective of this paper is to develop a dynamic emulator of a proton exchange membrane (PEM) electrolyzer (EL) through an equivalent electrical model. Experimental investigations have highlighted the capacitive effect of EL when subjecting t...
Simulation outputs from chemical transport models (CTMs) are essential to plan effective air quality policies. A key strength of these models is their ability to separate out source-specific components which facilitate the simulation of the potential...
This paper proposes new ANOVA-based approximations of functions and emulators of high-dimensional models using either available derivatives or local stochastic evaluations of such models. Our approach makes use of sensitivity indices to design adequa...
Physically-based radiative transfer models (RTMs) help in understanding the processes occurring on the Earth’s surface and their interactions with vegetation and atmosphere. When it comes to studying vegetation properties, RTMs allows us to study lig...
Developing a machine-learning-based radiative transfer emulator in a weather forecasting model is valuable because it can significantly improve the computational speed of forecasting severe weather events. To replace the radiative transfer parameteri...
Energy-economic simulation models with high levels of detail, high time resolutions, or large populations (e.g., distribution networks, households, electric vehicles, energy communities) are often limited due to their computational complexity. This p...
Physically-based radiative transfer models (RTMs) help understand the interactions of radiation with vegetation and atmosphere. However, advanced RTMs can be computationally burdensome, which makes them impractical in many real applications, especial...
Radiative transfer models (RTMs) are foundational to optical remote sensing for simulating vegetation and atmospheric properties. However, their significant computational cost, especially for 3D RTMs and large-scale applications, severely limits thei...
Reproducibility of experimental conditions is a fundamental requirement for designing energy efficient, self-sustainable wireless sensor networks (WSNs). At the same time, it represents a significant challenge because of the variability and the unpre...
This paper presents a power loss decrease method based on finite set model predictive control (FSMPC) with delay compensation for a motor emulator with reduced switch count. Specifically, the topology and mathematical model of the proposed motor emul...
Heating, ventilation, and air conditioning (HVAC) is the largest source of residential energy consumption. Occupancy sensors’ data can be used for HVAC control since it indicates the number of people in the building. HVAC and sensors form a typ...
Musculoskeletal models (MSKMs) are used to estimate the muscle and joint forces involved in human locomotion, often associated with the onset of degenerative musculoskeletal pathologies (e.g., osteoarthritis). Subject-specific MSKMs offer more accura...
The stylistic emulation of historical building facades presents significant challenges for artificial intelligence (AI), particularly for complex and data-scarce styles like Krakow’s Eclecticism. This study aims to develop a methodological fram...
Dual-motor Electric Drive Tracked Vehicles (DDTVs) have attracted increasing attention due to their high transmission efficiency and economical fuel consumption. A test bench for the development and validation of new DDTV technologies is necessary an...
While machine learning approaches are rapidly being applied to hydrologic problems, physics-informed approaches are still relatively rare. Many successful deep-learning applications have focused on point estimates of streamflow trained on stream gaug...
In recent years, advanced controllers, including Model Predictive Control (MPC), have emerged as promising solutions to improve the efficiency of building energy systems. This paper explores the capabilities of MPC in handling multiple control object...
A photovoltaic emulator (PVE) is a specialized device designed to mimic the static and dynamic properties of a solar panel. It serves as a crucial tool for testing and validating PV systems. Despite the unpredictable variations in real environmental...
In microgrid projects, social ownership involves aspects beyond their operation that may compromise the sustainability of the system. For this reason, the development of analysis methods to assess the feasibility and impact during the design stages o...
Advances in machine-learning techniques can serve practical water management needs such as salinity level estimation. This study explores machine learning, particularly deep-learning techniques in developing computer emulators for a commonly used pro...
Energy models require accurate calibration to deliver reliable predictions. This study offers statistical guidance for a systematic treatment of uncertainty before and during model calibration. Statistical emulation and history matching are introduce...
Developments in digital twins are driven by the availability of sensor technologies, big data, first principles knowledge, and advanced analytics. In this paper, we discuss these changes at a conceptual level, presenting a shift from nominal engineer...
Cyber-physical systems (CPSs) based on space-ground integrated networks (SGINs) enable CPSs to break through geographical restrictions in space. Therefore, providing a test platform is necessary for new technical verification and network security str...
Proton exchange membrane fuel cell (PEMFC) emulators are feasible solutions for conducting low-cost and safe developments. These types of systems have attracted the attention of global PEMFC manufacturers and research groups over the last few years....
Progress in advanced radiative transfer models (RTMs) led to an improved understanding of reflectance (R) and sun-induced chlorophyll fluorescence (SIF) emission throughout the leaf and canopy. Among advanced canopy RTMs that have been recently modif...
Applied tests on a real photovoltaic panel for a consolidated analysis require complex experiment setup and permanent availability of climatic conditions. This method is ineffective and can damage the PV system. As a result, PV emulators are highly r...
Electrolyzers (ELs) have become pivotal technologies for the production of green hydrogen, a clean energy carrier that facilitates renewable energy sources and supports the energy transition from fossil-based to a zero-carbon energy system. However,...
This paper presents the design of an innovative scalable wind turbine emulator. The system’s hardware and software components are described in detail including test results, demonstrating the research potential of the proposed design. The uniqu...
This paper deals with an emulation system for Power Electronics Converters (PEC). The emulation of PECs is performed on a Field-Programmable Gate Array (FPGA) capable of hard real-time operation. To obtain such a system, the converter operation is de...
Introduction: Traditional approaches to discover teleconnections and quantify uncertainty, such as global sensitivity analysis, Monte Carlo experiments, decomposition analysis, etc., are computationally intractable for large-scale process-based Coupl...
Traditional brain emulation approaches often rely on classical computational models that inadequately capture the stochastic, nonlinear, and potentially coherent features of biological neural systems. In this position paper, we introduce NeuroQ a qua...
In order to investigate the grid integration of wind turbines (WT) of various scales and designs, a wind turbine emulator (WTE) is being built in Flensburg within the state-funded project GrinSH. The special feature of this WTE is the use of a large...
Memristive devices have found application in both random access memory and neuromorphic circuits. In particular, it is known that their behavior resembles that of neuronal synapses. However, it is not simple to come by samples of memristors and adjus...
In this study, applicability of a data-driven Gaussian Process Emulator (GPE) technique to develop a dynamic surrogate model for a computationally expensive urban drainage simulator is investigated. Considering rainfall time series as the main drivin...
In this paper, a discrete non-stationary multiple-input multiple-output (MIMO) channel model suitable for the fixed-point realization on the field-programmable gate array (FPGA) hardware platform is proposed. On this basis, we develop a flexible hard...
The design and testing phase of photovoltaic (PV) power systems requires time-consuming and expensive field-testing activities for the proper operational evaluation of maximum power point trackers (MPPT), battery chargers, DC/AC inverters. Instead, t...
I propose a data-driven surrogate model for the In-Medium Similarity Renormalization Group (IMSRG) method using Dynamic Mode Decomposition (DMD). First, the Magnus formulation of the IMSRG is leveraged to represent the unitary transformation of many-...
Cybercriminals have become an imperative threat because they target the most valuable resource on earth, data. Organizations prepare against cyber attacks by creating Cyber Security Incident Response Teams (CSIRTs) that use various technologies to mo...
In recent years, the digital emulation of power systems, such as induction machines, has increased, driven by advances in computational resources and the processing capabilities of digital platforms. These platforms offer a versatile approach to the...
Knowledge of key variables driving the top of the atmosphere (TOA) radiance over a vegetated surface is an important step to derive biophysical variables from TOA radiance data, e.g., as observed by an optical satellite. Coupled leaf-canopy-atmospher...
A full smart grid implementation requires the digitization of all parts of the smart grid infrastructure, including secondary electrical substations. Unfortunately, this introduces new security threats, which were not apparent before. This article us...
This article presents the development of a power loss emulation (PLE) system device to study and find ways of mitigating skin tissue heating effects in transcutaneous energy transmission systems (TETS) for existing and next generation left ventricula...
Leaf wetness duration (LWD) has rarely been measured due to lack of standard protocol. Thus, empirical and physical models have been proposed to resolve this gap. Although the physical model provides robust performance in diverse conditions, it requi...
In recent years, nacelle test benches for wind turbines have been developed internationally. New standards are currently being developed that explicitly refer to the measurement of the electrical properties of wind turbines on these test benches. Thu...
This paper investigates modeling techniques for the mathematical representation of HV (high-voltage) Li-ion batteries to be used in conjunction with battery emulators for the test cell environment. To enable the impact of the battery response to be a...
This paper presents a method of implementing a 4 × 4 correlation matrix for evaluating the uplink channel properties of multiple-input multiple-output (MIMO) antennas using an over-the-air measurement system. First, the implementation model used to d...
The Integral Equation Model with multiple scattering (IEMM) represents a well-established method that provides a theoretical framework for the scattering of electromagnetic waves from rough surfaces. A critical aspect is the long computational time r...
Gaussian process emulators (GPE) are a machine learning approach that replicates computational demanding models using training runs of that model. Constructing such a surrogate is very challenging and, in the context of Bayesian inference, the traini...
The recent growing adversarial activity against critical systems, such as the power grid, has raised attention on the necessity of appropriate measures to manage the related risks. In this setting, our research focuses on developing tools for early d...
Integrated hydrologic models solve coupled mathematical equations that represent natural processes, including groundwater, unsaturated, and overland flow. However, these models are computationally expensive. It has been recently shown that machine le...
Fake identities have proven to be an effective methodology for conducting privacy and cybersecurity research; however, existing models are limited in their ability to interact with and respond to received communications. To perform privacy research i...
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