A5010295880- Advanced Control Systems Optimization
- Fault Detection and Control Systems
- Process Optimization and Integration
- Reservoir Engineering and Simulation Methods
- Oil and Gas Production Techniques
- Control Systems and Identification
- Extremum Seeking Control Systems
- Crystallography and Radiation Phenomena
- Advanced X-ray Imaging Techniques
- Integrated Energy Systems Optimization
- Neural Networks and Applications
- Viral Infectious Diseases and Gene Expression in Insects
- Probabilistic and Robust Engineering Design
- Hybrid Renewable Energy Systems
- Fuel Cells and Related Materials
- Building Energy and Comfort Optimization
- Advanced Optimization Algorithms Research
- Optimization and Variational Analysis
- Target Tracking and Data Fusion in Sensor Networks
- Offshore Engineering and Technologies
- Hydraulic Fracturing and Reservoir Analysis
- Model Reduction and Neural Networks
- Nuclear materials and radiation effects
- Electric Vehicles and Infrastructure
- Iterative Learning Control Systems
Norwegian University of Science and Technology
2015-2024
Kjemi (Norway)
2016-2022
École Polytechnique Fédérale de Lausanne
2017
Universidade Federal do Rio de Janeiro
2017
Universität Hamburg
1991-2003
Machine learning models are often considered as black-box solutions which is one of the main reasons why they still not widely used in operation process engineering systems. One approach to overcome this problem combine machine with first principles a system. In work, we investigate different methods combining and test them on case study multiphase flowrate estimation petroleum production However, can be applied any The results show that by adding physics-based learning, it possible only...
Data-driven solutions for multiphase flowrate estimation in oil and gas production systems are among the alternatives to first principles virtual flow metering hardware installations. Some of most popular data-driven methods this area based on artificial neural networks which have been proven be good tools. However, known sensitive scaling input data, difficult tune provide a black-box solution with occasionally unexplainable behavior under certain conditions. As an alternative, paper, we...
The motivation of this work is to propose a shared balance plant (BoP) and power supply (PS) design for industrial scale alkaline electrolyzer that has reduced CAPEX with minimum loss in OPEX variable load operation. Three important aspects are: a) flowsheet - either or individual BoP PS per stack, b) constant lye flowrate stack c) sizing cooling duty the circulation loop. Steady-state optimization shows (with higher CAPEX) optimal when expected operate at high capacity. For PS, hydrogen...
Stochastic processes are widely used to describe continuous degradation, among which the monotonically increasing degradation is most common. However, observation often perturbed with undesired noise due sensor or measurement errors in practice. This paper focuses on predicting growth and estimating system's remaining useful life based noisy observations. The deterioration modeled by a Transformed Gamma process, accounting for both time- state-dependent increments. Measurement error assumed...
The wavelength of the 57Fe Mössbauer radiation is measured with a relative uncertainty 0.19 ppm by using almost exact Bragg backscattering from reference silicon crystal. Its value determined as lambda(M) = 0.860 254 74(16)x10(-10) m. corresponding photon energy E(M) 14 412.497(3) eV. easily reproducible an accuracy at least 10(-11)lambda(M) and could be used length standard atomic dimensions.
Exact 180\ifmmode^\circ\else\textdegree\fi{} Bragg scattering of pulsed synchrotron radiation was observed by using a semitransparent detector and time-of-flight technique. The angular dependences monochromatic 14.413 keV x rays with only 0.5 $\ensuremath{\mu}$eV bandwidth were studied utilizing the $(13\overline{4}28)$ reflection an ${\mathrm{Al}}_{2}{\mathrm{O}}_{3}$ crystal at different temperatures. By heating first exact backscattering shows up achieving maximum intensity 1.7 mrad width...
Renewable energy sources have been the focal point to decarbonise power sector. The large deployment of these intermittent generation units requires mechanisms balance grid. Thermal plants can provide this service by increasing number start-ups, shut-downs, and intraday ramps at expense higher deterioration in critical equipment, including high-pressure steam drums, turbine rotors blades, high-temperature heat exchangers pipes. This work proposes a method formulate scheduling thermal as...
Neural differential equations have recently emerged as a flexible data-driven/hybrid approach to model time-series data. This work experimentally demonstrates that if the data contains oscillations, then standard fitting of neural equation may result in flattened out trajectory fails describe We introduce multiple shooting method and present successful demonstrations this for two datasets (synthetic experimental) fit. Constraints introduced by can be satisfied using penalty or augmented...
Most path-following algorithms for tracing a solution path of parametric nonlinear optimization problem are only certifiably convergent under strong regularity assumptions about the functions. In particular, linear independence constraint gradients at solutions is typically assumed, which implies unique multipliers. this paper we propose procedure designed to solve problems satisfying weaker set conditions, allowing nonunique (but bounded) Each iteration along consists three parts: (1)...
We present a sensitivity-based predictor-corrector path-following algorithm for fast nonlinear model predictive control (NMPC) and demonstrate it on large case study with an economic cost function. The method is applied within the advanced-step NMPC framework to obtain accurate approximate solutions of problem. In our approach, we solve sequence quadratic programs trace optimal solution along parameter change. A distinguishing feature in this paper that strongly-active inequality constraints...
Industrial waste heat recovery is an attractive option having the simultaneous benefits of reducing energy costs as well carbon emissions. In this context, thermal storage can be used along with optimal operation strategy like model predictive control (MPC) to realize significant savings. However, conventional methods offer little robustness against uncertainty in terms daily operation, where supply and demand cluster vary significantly from their predicted profiles. A major concern that...
An easy-to-implement noise estimation method for tuning state estimators is proposed. It outperforms benchmark methods in terms of accuracy or computational cost both theory and a case study. We assume parametric uncertainty the process model, which we transform into statistics using generalized unscented transformation (GenUT). While most other estimate only covariance, also mean. Our suitable input–output models, demonstrated through study involving simulators industrial data. present...