Richard D. Braatz

Automotive Engineering · 1997–2020

A researcher in the Science corpus: 20 papers; trusts 12 researchers and is trusted by 53 researchers here, as inferred from the citation graph.

Subfields

• Automotive Engineering — 104 citations into it
• Electrical and Electronic Engineering — 103 citations into it
• Control and Systems Engineering — 22 citations into it; #1,093 of 8,257 by trust here, #964 by citations
• Statistics and Probability — 11 citations into it; #7,176 of 12,932 by trust here, #8,279 by citations
• Optimization & Training — 8 citations into it
• Civil and Structural Engineering — 6 citations into it
• Statistical and Nonlinear Physics — 5 citations into it

Whom Richard D. Braatz trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Zoltan K. Nagy
2. Dongbin Xiu
3. Yurii E. Nesterov
4. John E. Dennis Jr.
5. Randall J. LeVeque
6. Dominique Bonvin
7. Gene H. Golub
8. Bruno Sudret
9. Thomas Kailath
10. Arkadi Nemirovski

Who trusts Richard D. Braatz overall

1. J. Urgen Schmidhuber
2. Chia-Feng Juang
3. Sashikumaar Ganesan
4. Jagdish Chandra Patra
5. Shen Yin
6. Zoltan K. Nagy
7. Ali Mesbah
8. José Maria P. Menezes
9. John E. Moody
10. Kwang-Ki K. Kim

Papers from Richard D. Braatz's perspective

Ordered by how strongly the researchers Richard D. Braatz trusts endorse each paper. Same corpus, a different order for every researcher.

1. A feedback-based implementation scheme for batch process optimization
2. The Wiener-Askey Polynomial Chaos for Stochastic Differential Equations (SIAM Journal on Scientific Computing)
3. An efficient, high-order perturbation approach for flow in random porous media via Karhunen-Loève and polynomial expansions
4. Global sensitivity analysis using polynomial chaos expansions (Reliability Engineering & System Safety)
5. Numerical Methods for Stochastic Computations: A Spectral Method Approach
6. Polynomial chaos expansion for sensitivity analysis (Reliability Engineering & System Safety)
7. Model predictive control: Theory and practice - A survey
8. Feedback and Optimal Sensitivity: Model Reference Transformations, Multiplicative Seminorms, and Approximate Inverses
9. Distributional uncertainty analysis using power series and polynomial chaos expansions
10. Dynamic optimization of batch processes: II. Role of measurements in handling uncertainty (Computers and Chemical Engineering)

Their papers

• Data-driven prediction of battery cycle life before capacity degradation (2019) — 2,606 citations
• Closed-loop optimization of fast-charging protocols for batteries with machine learning (2020) — 946 citations
• Modeling and Simulation of Lithium-Ion Batteries from a Systems Engineering Perspective (2012) — 701 citations
• High-Resolution Simulation of Multidimensional Crystal Growth (2002) — 159 citations
• Solute concentration prediction using chemometrics and ATR-FTIR spectroscopy (2001) — 139 citations
• Distributional uncertainty analysis using power series and polynomial chaos expansions (2007) — 194 citations
• Optimal control and simulation of multidimensional crystallization processes (2002) — 164 citations
• Constrained zonotopes: A new tool for set-based estimation and fault detection (2016) — 380 citations
• Active Fault Diagnosis for Nonlinear Systems with Probabilistic Uncertainties (2014) — 57 citations
• Wiener's Polynomial Chaos for the Analysis and Control of Nonlinear Dynamical Systems with Probabilistic Uncertainties [Historical Perspectives] (2013) — 107 citations
• Advances and new directions in crystallization control. (2012) — 322 citations
• Comparative performance of concentration and temperature controlled batch crystallizations (2008) — 167 citations
• High resolution algorithms for multidimensional population balance equations (2004) — 310 citations
• Robust nonlinear model predictive control of batch processes (2003) — 311 citations
• Fault Detection and Diagnosis in Industrial Systems (2001) — 1,138 citations
• Fault detection in industrial processes using canonical variate analysis and dynamic principal component analysis (2000) — 490 citations
• Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes (2000) — 337 citations
• Fault diagnosis in chemical processes using Fisher discriminant analysis, discriminant partial least squares, and principal component analysis (2000) — 598 citations
• A tutorial on linear and bilinear matrix inequalities (2000) — 632 citations
• On the "Identification and control of dynamical systems using neural networks" (1997)