arXiv subjects

Mohammad Hemmati

Publications and source records attributed to Mohammad Hemmati.

5 recordsLinked to original sources

arXiv2026

Powering the Future of AI: Navigating the Trade-offs for Europe's Energy Transition and Net-Zero Goals

The rapid expansion of AI globally has led to the proliferation of energy-intensive hyperscale data centres (DCs), making them as a structurally challenging component in power system planning and operation. Using a spatially explicit optimisation model of Europe across 21 AI growth scenarios, we systematically quantify additional demand, capacity requirements, emissions, and operational impacts of DCs. Results indicate that AI could drive 73-723 TWh of extra demand by 2050, risking cumulative emissions overshoots of 67-181 MtCO2 between 2030 and 2050. Our analysis indicates that after 2030, the geography of AI infrastructure will be shaped more by firm power and system flexibility than by the mere abundance of clean energy. In moderate scenarios, AI requires an additional of 200 hours of firm generation, which increases LCOE by 35 EUR/MWh in key hubs. We show that even under the pessimistic scenarios, existing infrastructure would require 70 GW additional capacity, while under managed growth pathways, this expansion could reach 226 GW. We further find DCs workload dynamics strongly shape energy dispatch, system flexibility, and emissions, while improved efficiency significantly reduces capacity needs, and system peaks. While our findings suggest that net-zero targets for 2050 may be achieved, critical emission risks may appear in the intermediate years, and the EU may compromise its carbon-neutral goals unless policies adapt to this accelerating digital transformation.

math.OC↗

arXiv2023

Density-functional description of materials for topological qubits and superconducting spintronics

Interfacing superconductors with magnetic or topological materials offers a playground where novel phenomena like topological superconductivity, Majorana zero modes, or superconducting spintronics are emerging. In this work, we discuss recent developments in the Kohn-Sham Bogoliubov-de Gennes method, which allows to perform material-specific simulations of complex superconducting heterostructures on the basis of density functional theory. As a model system we study magnetically-doped Pb. In our analysis we focus on the interplay of magnetism and superconductivity. This combination leads to Yu-Shiba-Rusinov (YSR) in-gap bound states at magnetic defects and the breakdown of superconductivity at larger impurity concentrations. Moreover, the influence of spin-orbit coupling and on orbital splitting of YSR states as well as the appearance of a triplet component in the order parameter is discussed. These effects can be exploited in S/F/S-type devices (S=superconductor, F=ferromagnet) in the field of superconducting spintronics.

cond-mat.supr-con↗

arXiv2020

ECG-Based Blood Pressure Estimation Using Mechano-Electric Coupling Concept

The Electrocardiograph signal represents the heart's electrical activity while blood pressure results from the heart's mechanical activity. Previous studies have investigated how the heart's electrical and mechanical activities are related and have referred to their relationship as the Mechano-Electric Coupling term. A new method to estimate the blood pressure including is proposed which uses only the Electrocardiograph signal. In spite of studies performed on feature extraction based on the signals' physiological parameters (Parameter-based), in this work, the feature vectors are formed with samples of the Electrocardiograph signal in a particular time frame (Whole-based) and these vectors are input into Adaptive Boosting Regression to estimate blood pressure. The nonlinear relationship which correlates blood pressure with the Electrocardiograph signal is concluded by the results of this study. According to the results, the used algorithms, for estimating both diastolic blood pressures and mean arterial pressure, are in compliance with the standards of the Association for the Advancement of Medical Instrumentation. Also, according to the British Hypertension Society standard, estimating diastolic blood pressures and mean arterial pressure with the proposed method attain an A grade while it achieves B for systolic blood pressure. The results indicate that using the introduced method, blood pressure can be estimated continuously, noninvasively, without cuff, calibration-free and by using only the Electrocardiograph signal.

eess.SP↗

arXiv2019

Uncertainty Management in Power System Operation Decision Making

Due to the penetration of renewable energy resources and load deviation, uncertainty handling is one of the main challenges for power system; therefore the need for accurate decision-making in a power system under the penetration of uncertainties is essential. However, decision makers should use suitable methods for uncertainty management. In this chapter, some of the uncertainty modeling methods in power system studies are analyzed. At first, multiple uncertain parameters that the power system deals with are introduced, then some useful uncertainty modeling methods are introduced. To show the uncertainty modeling process and its effect on the decision-making, a microgrid consisting of multiple uncertain parameters is considered, and stochastic scenario-based approach is used for uncertainty modeling. The scheduling of microgrids in the presence of different types of uncertainty is solved from the profit-maximization point of view. The simulation results are presented for a 33-bus microgrid that shows the effectiveness of the proposed method for decision-making under high level of uncertainty.

eess.SY↗

arXiv2019

A Configurable Memristor-based Finite Impulse Response Filter

There are two main methods to implement FIR filters: software and hardware. In the software method, an FIR filter can be implemented within the processor by programming; it uses too much memory and it is extremely time-consuming while it gives the design more configurability. In most hardware-based implementations of FIR filters, Analog-to-Digital (A/D) and Digital-to-Analog (D/A) converters are mandatory and increase the cost. The most important advantage of hardware implementation of a FIR filter is its higher speed compared to its software counterpart. In this work, considering the advantages of software and hardware approaches, a method to implement direct form FIR filters using analog components and memristors is proposed. Not only the A/D and D/A converters are omitted, but also using memristors avails configurability. A new circuit is presented to handle negative coefficients of the filter and memristance values are calculated using a heuristic method in order to achieve a better accuracy in setting coefficients. Moreover, an appropriate sample and delay topology is employed which overcomes the limitations of the previous research in implementation of high-order filters. Proper operation and usefulness of the proposed structures are all validated via simulation in Cadence.

eess.SP↗