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Understanding the energy and emission implications of new technologies in a kraft mill: Insights from a CADSIM Plus simulation model

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TAPPI JOURNAL 2024年第6期23卷 336-351页

作者： Rogerson, Adam Savulescu, Luciana Bernier, Etienne Bedard, Serge Industrial Process Decarbonization Industrial Systems Optimization Group for Natural Resources Canada CanmetENERGY

Kraft mills play a vital role in energy transition because they have significant potential to reduce their own energy utilization and produce energy/products to decarbonize other sectors. Through biomass combus-tion and potential biogenic carbon emissions capture, these mills can contribute to offsetting emissions from other sectors. This research investigates the departmental and cross-departmental implications of technology upgrades on energy, steam, emissions, water, and chemicals using a CADSIM Plus simulation model. The model provides a com-prehensive analysis of mass and energy balances, offering valuable insights into the benefits and limitations of each technology. The model facilitates scenario analysis and comparisons of process configurations, enabling data-driven decision-making for sustainable and competitive operations. Six high-impact technologies, including additional evaporator effects, weak black liquor membrane concentra-tion, belt displacement washer for brownstock washing, oxygen delignification, and improvements to the pulp machine shoe press and vacuum pumps, are evaluated. Individual technologies resulted in energy savings of 1.2% to 5.4%, biomass consumption reductions of 8.6% to 31.6%, and total emissions reductions of 1.6% to 5.9%. Strategic decision-making must consider existing mill limitations, future technology implementation, and potential production increases. Future research will explore product diversification, biorefineries, and pathways to achieve carbon-nega-tive operations, aiming to reduce emissions and secure a competitive future for kraft mills. Application: A mill-wide simulation model has been developed to evaluate various technologies, taking into account the complex and interconnected nature of the kraft recovery cycle. This simulation provides a comprehen-sive assessment of each technology, considering their effects on energy, steam, emissions, water, chemicals, and economics.

关键词： Energy utilization

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CLF3D: A Coarse-Labeling Framework to Facilitate 3D Object Detection in Point Clouds

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IEEE Access 2025年 13卷 105753-105765页

作者： Nuo Cheng Chuanyu Luo Han Li Sikun Ma Shengguang Lei Pu Li Process Optimization Group Technische Universität Ilmenau Ilmenau Germany LiangDao GmbH Berlin Germany

Tremendous scenarios have to be considered for autonomous driving, leading to extremely large amount of point cloud data which need to be labeled for model training. Manually labeling such data is labor-intensive and highly expensive. In this paper, we propose CLF3D, a simple and effective coarse-labeling framework designed to improve existing automated labeling methods by fully leveraging scene-specific information in the unlabeled data to significantly enhance detection accuracy. Specifically, CLF3D first utilizes a pre-trained model to generate initial pseudo-labels, which are subsequently refined using a two-stage filtering strategy in combination with an instance bank built from high-quality annotated instances. These refined pseudo-labels are then used to fine-tune the model, progressively improving its detection performance on unlabeled data. Through iterative refinement of pseudo-labels, the model parameters, and the instance bank, CLF3D continuously improves label quality and accuracy. Experimental results demonstrate that the proposed method improves the detection accuracy by up to 14% compared to the originally pre-trained model across datasets of various sizes. This means our approach can reduce 14% of the manual workload for labeling point cloud data in comparison to the existing methods.

关键词： Annotations Labeling Data models Point cloud compression Manuals Accuracy Three-dimensional displays Object detection Autonomous vehicles Training

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Optimal Sensor Placement and PRV Localization under Demand Uncertainty

Optimal Sensor Placement and PRV Localization under Demand U...

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World Environmental and Water Resources Congress 2025: Cool Solutions to Hot Topics

作者： Korder, Kristina Salomons, Elad Ostfeld, Avi Li, Pu Process Optimization Group Institute of Automation and Systems Engineering Technical Univ. Ilmenau Ilmenau Germany Faculty of Civil and Environmental Engineering Technion-Israel Institute of Technology Haifa Israel

ISBN: (数字)9780784486184

ISBN: (纸本)9780784486184

The implementation of real-time pressure management requires the acquisition of online measurement data, which is essential for the design of a closed-loop control system. In order to achieve this, it is necessary to determine in advance the locations for the installation of pressure sensors and pressure reducing valves (PRVs) for pressure reduction and control in a water distribution system (WDS). The sensors should be positioned at the most sensitive points to pressure variation, while the PRVs should be located at the points with the largest pressure drops. In this study, we solve this problem by extending an existing deterministic approach to a stochastic one with uncertain demand. For this purpose, we use the gap statistic to determine the number of sub-regions, the k-means++ to select the sensor positions, an edge-selection scheme for PRV localization, and differential evolution to minimize the total operating pressure. More importantly, we propose a scheme to calculate the sensitivity of the pressure and the pressure reduction due to the variation of the demand, based on which the formulated optimization is solved. Furthermore, the satisfaction of operational constraints, such as ensuring the pressure lower and upper bounds in the network, is formulated as chance constraints. Finally, a two-stage optimization framework is developed to solve this problem. In the lower level, Monte Carlo simulation is used to evaluate the impact of the uncertainties on the WDS performance. In the upper level, an optimizer determines the optimal locations for the pressure sensors and PRVs. © 2025 ASCE.

关键词： Monte Carlo methods

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PSCO: A Point Cloud Scene Classification Model Based on Contrast Learning

PSCO: A Point Cloud Scene Classification Model Based on Cont...

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IEEE International Conference on Image processing

作者： Nuo Cheng Xiaohan Li Chuanyu Luo Xiaotong Liu Han Li Shengguang Lei Pu Li Process Optimization Group Technische Universitat Ilmenau Ilmenau Germany LiangDao GmbH Berlin Germany

Point cloud LiDAR data are increasingly used for detecting road situations for autonomous driving. As data acquisition is much cheaper than data annotation, the classification of the collected data and selecting a part of it for annotation is an important pre-processing step. In this study, we propose a self-supervised method and a corresponding package (PSCO) to classify driving scenes in large-scale point cloud data. We propose a contrastive learning approach which encodes each single frame of the collected raw data into a feature vector that can be effectively classified. Using this approach, the number of necessary frames for annotation to train scene-based models can be significantly reduced. In addition, our method can also select specific scenario data for different individual training stages.

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Rethinking Masked-Autoencoder-Based 3D Point Cloud Pretraining

Rethinking Masked-Autoencoder-Based 3D Point Cloud Pretraini...

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IEEE Symposium on Intelligent Vehicle

作者： Nuo Cheng Chuanyu Luo Xinzhe Li Ruizhi Hu Han Li Sikun Ma Zhong Ren Haipeng Jiang Xiaohan Li Shengguang Lei Pu Li Process Optimization Group Technische Universität Ilmenau Ilmenau Germany LiangDao GmbH Berlin Germany Great Wall Motor Co. Ltd. China

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

The BERT-style (Bidirectional Encoder Representations from Transformers) pre-training paradigm has achieved remarkable success in both NLP (Natural Language processing) and CV (Computer Vision). However, due to the sparsity and lack of semantic information in point cloud data, directly applying this paradigm faces significant obstacles. To address these issues, we propose LSV-MAE, a masked autoencoding pre-training scheme designed for voxel representations. We pre-train the backbone to reconstruct the masked voxels features extracted by PointNN. To enhance the feature extraction capability of the encoder, the point cloud is voxelized with different voxel sizes at different pre-training stages. Meanwhile, to minimize the effect of masking key points during the masking stage, the masked voxel features is re-integrated during the decoder processing. To test the proposed approach, experiments are conducted on well-known datasets. It is shown that the proposed method can improve detection accuracy by 1% to 18%, compared to the model without pre-training, across datasets of different sizes.

关键词： Point cloud compression Training Three-dimensional displays Semantics Feature extraction Transformers Natural language processing

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Chance Constrained Distributed Optimisation for Interconnected Power Systems ⁎

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IFAC-PapersOnLine 2024年第13期58卷 128-133页

作者： Ineza Remy Mugenga Abebe Geletu Pu Li African Institute of Mathematical Sciences (AIMS) Rwanda P.O. Box: 7150 Kigali Rwanda Group of Process Optimization Institute for Automation and Systems Engineering Technische Universität Ilmenau P.O. Box 100565 98684 Ilmenau Germany

Microgrids have been attracted increasingly attention due to renewable energy integration. Multiple microgrids are often interconnected for benefiting each other. A significant challenge in operating such power systems lies in the uncertainties including intermittence in renewable energy sources and load demands estimation. Sharing state variables in interconnected systems poses additional difficulties. This paper proposes a numerical solution approach to a chance constrained distributed optimisation for interconnected power systems under uncertainty. The inner-outer approximation approach is used for the solution and ALADIN for numerical implementation. An interconnected optimal power flow problem with a three-bus and a four-bus system is solved as a case study.

关键词： Interconnecting microgrids shared state systems distributed algorithms ALADIN chance constraints inner-outer approximation

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Establishing an Experimental and Simulation Interface for Online Monitoring and Modeling of Bacterial Growth in Water Distribution Systems

Establishing an Experimental and Simulation Interface for On...

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World Environmental and Water Resources Congress 2022: Adaptive Planning and Design in an Age of Risk and Uncertainty

作者： Kadinski, Leonid Schuster, Jonas Abhijith, Gopinathan R. Hao, Cao Grieb, Anissa Pu, Li Ernst, Mathias Ostfeld, Avi Faculty of Civil and Environmental Engineering Technion-Israel Institute of Technology Haifa Israel Institute For Water Resources and Water Supply Hamburg Univ. of Technology Hamburg Germany Process Optimization Group Institute of Automation and Systems Engineering Technical Univ. Ilmenau Ilmenau Germany

ISBN: (数字)9780784484258

ISBN: (纸本)9780784484258

Water distribution systems (WDSs) function to deliver high-quality water in major quantities. While standard water quality parameters are monitored at waterworks, it is still a challenge to monitor water quality in the WDS network itself. Only hydraulic parameters are frequently monitored and modeled in drinking water networks in Germany. Moreover, the majority of German drinking water utilities does not disinfect when the product leaves the waterworks. This is also common practice in Northern European countries. It is thus important to monitor specific organic and bacteriological water quality parameters which define the system state. This study develops an experimental and simulation integrated framework for continuously monitoring and simulating selected organic and bacteriological water quality parameters, so abnormal deviations in water quality behavior can be detected and responded to in real time. A simple reproducible bacteria regrowth model was taken to initialize the validation of experimental values in a water quality model simulation. Batch experiment measurements from a flow cytometer are analyzed to establish an interface between laboratory values and water quality simulations. Monod kinetics are utilized to describe the bacterial growth rate according to the respective substrate for modeling the bulk species in the water network. Experimental values are incorporated in the simulations for validation. The simulation of bacterial growth is conducted firstly on a network model of a real-life test bed and on various selected distribution system models of different sizes and complexities. First results of the water quality simulations show a successful transition of experimental analysis into water quality simulations and give a promising outlook for developing an online-monitoring and prediction methodology for detecting water quality anomalies efficiently in real time. © ASCE.

关键词： Water quality

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Optimal Control of Chlorine Concentration in Water Distribution System

Optimal Control of Chlorine Concentration in Water Distribut...

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World Environmental and Water Resources Congress 2022: Adaptive Planning and Design in an Age of Risk and Uncertainty

作者： Cao, Hao Schuster, Jonas Kadinski, Leonid Abhijith, Gopinathan R. Grieb, Anissa Ernst, Mathias Ostfeld, Avi Li, Pu Process Optimization Group Institute of Automation and Systems Engineering Technical Univ. Ilmenau Ilmenau Germany Institute of Water Resources and Water Supply Hamburg Univ. of Technology Hamburg Germany Faculty of Civil and Environmental Engineering Technion-Israel Institute of Technology Haifa Israel

ISBN: (数字)9780784484258

ISBN: (纸本)9780784484258

Supplying high-quality water is the key task of water distribution systems (WDSs). Although in Germany and some other countries chlorine is no longer used, it remains as a major disinfectant in WDSs worldwide. Therefore, chlorine concentration represents an important parameter for determining the water quality;that is, we should ensure the chlorine concentration within a reasonable range in a WDS. However, due to the complexity of the network structure and nonlinear behavior of the system, the control of chlorine concentration in WDSs imposes a challenging task. In this study, a model-based optimal control strategy is developed to address this problem. The mass and energy conservation laws are used to describe the hydraulic properties of WDSs. The one-dimensional advective transport model is simplified to describe the decay of chlorine in the pipelines. The chlorine concentration limits at the nodes are formulated as inequality constraints which will be satisfied by manipulating the flows and their directions in the pipelines. As a result, a nonlinear optimization problem is formulated and solved to achieve the specified chlorine concentration. For verifying our approach, we deliver the computed results for benchmark networks as input to the simulation model in EPANET, and the simulation gives satisfactory values of the specified chlorine concentration in the network. © ASCE.

关键词： Water distribution systems

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Prediction of medium-to-coal ratio effect in a dense medium cyclone by using both traditional and coarse-grained CFD-DEM models

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Particuology 2022年第9期20卷 44-56页

作者： Zhaoyang Li Kaiwei Chu Zongqing Zhou Yixiong Feng Aimin Wang School of Mechanical Engineering Zhejiang UniversityHangzhou 310027China School of Qilu Transportation Shandong UniversityJinan 250002China Shandong Iron and Steel Group Co. Ltd.Jinan 250101China State Key Lab Fluid Power&Mechatron Syst Zhejiang UniversityHangzhou 310027China4.Hengda Fuji Elevator Co.Ltd.Huzhou 313009China JITRI Institute for Process Modelling and Optimization Suzhou 215123China

Dense medium cyclone(DMC)is the working horse in coal *** practice,it is usually operated under constant pressure and the operational conditions(mainly medium-to-coal(M:C)ratio and oper-ational pressure)need to be adjusted according to coal washability data(mainly coal particle size and density distributions).Nonetheless,until now it is still not well understood how the M:C ratio would affect the performance of DMCs especially under the practical *** this work,the effect of M:C ratio is for the first time numerically studied under conditions similar to plant operation by using both tra-ditional and coarse-grained(CG)combined approach of computational fluid dynamics(CFD)and discrete element method(DEM),called as traditional CFD-DEM and CG CFD-DEM,in which the flow of coal par-ticles is modelled by DEM or CG DEM which applies Newton's laws of motion to individual particles and that of medium flow by the conventional CFD which solves the local-averaged Navier-Stokes equations,allowing consideration of particle-fluid mutual interaction and particle-particle ***,impulse and momentum connection law is used to achieve energy conservation between traditional CFD-DEM and CG *** is found that under constant pressure,the M:C ratio affects DMC perfor-mance *** specific effect depends on coal washability or coal *** extremely low M:C ratio,the phenomenon that high-quality coal product is misplaced to reject is successfully repro-duced,which has been observed in plants in Australian coal industry and called as"low-density tail".Moreover,strategies are proposed to mitigate the"low-density tail"phenomenon based on the model.

关键词： Dense medium cyclone Medium-to-coal ratio Discrete element method Computational fluid dynamics Low-density coal tail

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Indistinguishability analysis and observer design for size-structured cell populations

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IFAC-PapersOnLine 2023年第2期56卷 581-586页

作者： P. Jerono J.J. Winkin A. Vande Wouwer A. Schaum Digital Process Engineering Group (DPE) Karlsruhe Institute of Technology Germany Department of Mathematics and Institute for Complex Systems (naXys) University of Namur Belgium Systems Estimation Control and Optimization (SECO) University of Mons Belgium Chair of Automation and Control (ACON) Kiel University Germany

The observability property of population balance equations with biomass measurements is addressed within the framework of indistinguishable trajectories. The population balance equation is described by a partial integro-differential equation which is coupled with an ordinary differential equation for the nutrient dynamics. For the semi-discretized model equations, the dynamics of indistinguishable trajectories are derived and evaluated for the special case of equal partitioning at cell division revealing that the observability property is guaranteed as long as the nutrient concentration is not depleted. Based on these results, an observer is designed and tested in simulation to estimate the cell population distribution using biomass measurements in a batch bioreactor for the case of a bi-structured population.

关键词： Observability indistinguishable trajectories cell population dynamics

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