Results 51 to 60 of about 10,522,925 (246)
The iron and steel industry, a major energy consumer, faces significant pressure to reduce CO2 emissions. As the world’s largest steel producer, China must prioritize this sector to meet its carbon neutrality goals.
Tianshu Hou, Yuxing Yuan, Hongming Na
doaj +1 more source
The role of nanocatalyst of pearl oyster shell in pack carburizing process on mechanical and physical properties of AISI 1020 steel [PDF]
The most commonly used metal material in the industry today is steel. Steel is classified based on its carbon content. There are high-carbon steel, medium-carbon steel, and low-carbon steel.
Rafi Muhammad +2 more
doaj +1 more source
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
Optimization of the Production of Rubber Compounds Using Mathematical Models
Rubber compounds were mixed in a batch internal mixer, and symbolic regression was used to derive mathematical models linking recipe and process parameters to ram path, torque, and mixing quality (incorporation, dispersion, distribution). Subsequent optimization with evolutionary algorithms identified operating conditions that reduce specific energy ...
Anke Bardehle +7 more
wiley +1 more source
The agglomeration behavior of non-metallic inclusion is a critical phenomenon that needs to be controlled as it has a direct relationship with the performance of produced steel.
Yasuhiro Tanaka +2 more
doaj +1 more source
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
CRGTNet: Wear identification in in-service control rod guide tubes via convolutional neural networks
The wear of the control rod guide tube can lead to an increasing in the drop-time of control rods, causing nuclear reactor accidents. When using machine vision methods to identify worn holes, the similarity in appearance between worn and unworn holes due
Xueting Sun +5 more
doaj +1 more source
Experiments and thermophysical simulations were conducted to investigate the electron beam powder bed fusion electron beam (PBF‐EB/M) process for the γ′‐strengthened nickel‐based superalloy Inconel 738LC. The results demonstrate the impact of process‐induced microstructural variations on high‐temperature mechanical behavior, providing a basis for ...
Jan Niklas Petenati +11 more
wiley +1 more source
Extremely low cycle fatigue tests on structural carbon steel and stainless steel [PDF]
Cyclic material tests in the low and extremely low cycle fatigue regime were carried out to study the properties of structural carbon steel and stainless steel.
Gardner, L +3 more
core +1 more source
Schematic representation of modes of microcrack nucleation, growth and temporary arrestment at different boundaries, with the criteria for crack propagation in three scenarios: (1) large notch, (2) defect/small sharp notch, and (3) long crack. This work revisits and integrates results on the fatigue behavior of advanced bainitic steels (in particular ...
Lucia Morales‐Rivas
wiley +1 more source

