Results 91 to 100 of about 228,376 (312)

Combined use of long short‐term memory neural network and quantum computation for hierarchical forecasting of locational marginal prices

open access: yesEnergy Conversion and Economics
Accurate locational marginal price forecasting (LMPF) is crucial for the efficient allocation of resources. Nevertheless, the sudden changes in LMP make it inadequate for many existing long short‐term memory (LSTM) network‐based prediction models to ...
Xin Huang   +6 more
doaj   +1 more source

Design and simulation of submarine dual-mode SOFC-MGT hybrid power generation system

open access: yesZhongguo Jianchuan Yanjiu, 2019
[Objectives] Solid Oxide Fuel Cell-Micro Gas Turbine(SOFC-MGT) hybrid power generation system will help to improve the endurance and stealth of conventionally powered submarines.
ZHU Runkai   +4 more
doaj   +1 more source

The Capacity Optimization of Hybrid Energy Storage System for Wind Power Smoothing

open access: yes, 2014
Wind power system plays an important role insmoothing wind power fluctuations. In consideration of limitedadvantage of single energy storing dielectric, the hybrid energystorage system has a good application prospect with its meritscomplementation.
Bingliang Zhang   +6 more
core  

Performance Analysis of Hybrid and Full Electrical Vehicles Equipped with Continuously Variable Transmissions [PDF]

open access: yes, 2013
The main aim of this paper is to study the potential impacts in hybrid and full electrical vehicles performance by utilising continuously variable transmissions. This is achieved by two stages.
Trimble, Robert   +5 more
core   +1 more source

Low Cycle Repetitive Loading of Ti‐6Al‐4V‐Epoxy Composite Lattice Structures for Enhanced Energy Dissipation and Damage Tolerance

open access: yesAdvanced Engineering Materials, EarlyView.
Composite Ti–6Al–4V–epoxy lattice structures are additively manufactured and epoxy infiltrated for cyclic loading. At low lattice volume fractions, hybridization produces synergistic gains in stiffness and energy dissipation. At higher volume fractions, synergy diminishes, although composites still exceed metallic lattices in specific energy ...
Joey Tallon   +3 more
wiley   +1 more source

From Shear to Sound: Mechanics–Acoustics Mapping of TPMS Lattices

open access: yesAdvanced Engineering Materials, EarlyView.
Triply periodic minimal surface (TPMS) lattices are mapped across mechanical and acoustic performance, revealing that descriptors validated in compression fail under shear. First‐time comparison with trusses included. A transition from porous to resonance‐driven absorption emerges at 25% density.
Lucía Doyle   +3 more
wiley   +1 more source

Power Management in PVWindBattery Based Hybrid Power System [PDF]

open access: yesInternational Journal of Trend in Scientific Research and Development, 2018
The battery energy storage system BESS is one of the main means of smoothing wind or solar power generation fluctuations. Such BESS based hybrid power systems require a suitable control strategy that can effectively regulate power output levels and battery state of charge SOC . This paper presents the results of a wind photovoltaic PV BESS hybrid power
openaire   +1 more source

Designing Polymer Nanocomposites for X‐Ray Shielding: Mechanisms, Architectures, and Scalable Processing

open access: yesAdvanced Engineering Materials, EarlyView.
This review highlights advances in lightweight, lead‐free polymer nanocomposites for diagnostic X‐ray shielding. By linking filler chemistry, dispersion, architecture, and photon interaction mechanisms, it establishes structure–performance relationships guiding material design.
Aklilu G. Messele   +2 more
wiley   +1 more source

The Optimization of Hybrid Power Systems with Renewable Energy and Hydrogen Generation

open access: yesEnergies, 2018
This paper discusses the optimization of hybrid power systems, which consist of solar cells, wind turbines, fuel cells, hydrogen electrolysis, chemical hydrogen generation, and batteries.
Fu-Cheng Wang   +2 more
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

open access: yesAdvanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer   +4 more
wiley   +1 more source

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