Results 141 to 150 of about 6,357,366 (292)
DSCostPred: a double-stacking model for construction cost prediction. [PDF]
Liu CP, Sun XG, Guan JH.
europepmc +1 more source
Copper‐based composites enhanced with carbon feature convenient mechanical properties and favorable electric conductivity. Processing via deformation and thermomechanical treatments can introduce advantageous microstructures further enhancing their performance. Herein, copper–graphene powder‐based composites are directly consolidated via rotary swaging
Radim Kocich +3 more
wiley +1 more source
Uncertainty aware and explainable construction cost prediction using a hybrid probabilistic learning model. [PDF]
Chen L +7 more
europepmc +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
Hybrid metaheuristic optimized Catboost models for construction cost estimation of concrete solid slabs. [PDF]
Elmasry NH, Elshaarawy MK.
europepmc +1 more source
Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara +8 more
wiley +1 more source
Construction cost prediction model for agricultural water conservancy engineering based on BIM and neural network. [PDF]
Han K +5 more
europepmc +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
Intelligent building construction cost optimization and prediction by integrating BIM and elman neural network. [PDF]
Zhang Y, Mo H.
europepmc +1 more source
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source

