Special section on multidisciplinary design optimization: metamodeling in multidisciplinary design optimization: how far have we really come?

FAC Viana, TW Simpson, V Balabanov, V Toropov - AIAA journal, 2014 - arc.aiaa.org
The use of metamodeling techniques in the design and analysis of computer experiments
has progressed remarkably in the past 25 years, but how far has the field really come? This …

Modeling process–structure–property relationships in metal additive manufacturing: a review on physics-driven versus data-driven approaches

N Kouraytem, X Li, W Tan, B Kappes… - Journal of Physics …, 2021 - iopscience.iop.org
Metal additive manufacturing (AM) presents advantages such as increased complexity for a
lower part cost and part consolidation compared to traditional manufacturing. The multiscale …

Artificial intelligence/machine learning in manufacturing and inspection: A GE perspective

KS Aggour, VK Gupta, D Ruscitto, L Ajdelsztajn… - MRS …, 2019 - cambridge.org
At GE Research, we are combining “physics” with artificial intelligence and machine learning
to advance manufacturing design, processing, and inspection, turning innovative …

A methodology for calibration of building energy models at district scale using clustering and surrogate techniques

G Tardioli, A Narayan, R Kerrigan, M Oates… - Energy and …, 2020 - Elsevier
Prediction of building energy use, when performed at urban scale, is influenced by the
choice of modelling approach, as well as the quality of available data. In the case of data …

Federated multimodal big data storage & analytics platform for additive manufacturing

KS Aggour, VS Kumar, P Cuddihy… - … conference on big …, 2019 - ieeexplore.ieee.org
Additive technologies are expected to revolutionize manufacturing across almost every
industry, but there is a sizable gap between the current state of the technology and the …

On Uncertainty Quantification in Materials Modeling and Discovery: Applications of GE's BHM and IDACE

SK Ravi, A Bhaduri, A Amer, S Ghosh, L Wang… - AIAA SCITECH 2023 …, 2023 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2023-0528. vid The coupling of artificial
intelligence and materials characterizations has been a center piece of almost all materials …

Industrial applications of intelligent adaptive sampling methods for multi-objective optimization

J Kristensen, W Subber, Y Zhang… - Design and …, 2019 - books.google.com
Multi-objective optimization is an essential component of nearly all engineering design.
However, for industrial applications, the design process typically demands running …

Calibrating transient models with multiple responses using Bayesian inverse techniques

NC Kumar, AK Subramaniyan… - … Expo: Power for …, 2013 - asmedigitalcollection.asme.org
Several engineering applications of high interest to turbomachinery involve transient models
with multiple outputs. Thus, the ability to calibrate transient models with multiple correlated …

The effect of grid resolution and reaction models in simulation of a fluidized bed gasifier through nonintrusive uncertainty quantification techniques

M Shahnam, A Gel, JF Dietiker… - Journal of …, 2016 - asmedigitalcollection.asme.org
To improve quality of numerical models used in simulations of a fluidized bed gasifier at any
scale, the sources of uncertainty in the simulation have to be identified and quantified. There …

A gaussian process modeling approach for fast robust design with uncertain inputs

KM Ryan, J Kristensen, Y Ling… - … Expo: Power for …, 2018 - asmedigitalcollection.asme.org
Many engineering design and industrial manufacturing applications are tasked with finding
optimum designs while dealing with uncertainty in the design parameters. The performance …