Energy Dissipation Characteristics Modelling for Hot Extrusion Forming of Aluminum-Alloy Components

Hongcheng Li,Yuanjie Wu,Huajun Cao,Feng Lu,Congbo Li 한국정밀공학회 2022 International Journal of Precision Engineering and Vol.9 No.6

The hot extrusion forming process is widely used to process aluminum-alloy components in both the automobile and aircraft manufacturing industries. Since it involves pushing the material through the die at increased temperature, it is very energy-intensive despite requiring less blank material allowance. During hot extrusion forming, the multi-stage dynamic conversion of electricity, mechanical energy, and hydraulic energy to heat results in high energy dissipation. In order to improve the power and energy conversion efficiency of hot extrusion forming process, it is necessary to identify the energy dissipation characteristics. The transfer and conversion paths of the electrical, mechanical, and hydraulic energy from the motor to the hydraulic cylinder were firstly depicted based on the motion cycle of the extruder. A bond graph-based energy dissipation model was then proposed for dynamically identifying the energy-saving potentials. The energy dissipation model integrated the power bond graph sub-model of energy conversion elements such as motor, pump, hydraulic valve group, and hydraulic cylinder. These power bond graph sub-models were separately developed to find the energy dissipation state equations of energy conversion elements. An experiment was carried out using data obtained from the energy management system to validate the bond graph-based energy dissipation model. The results have shown that the power and energy conversion efficiency of hot extrusion forming is primarily controlled by the parameters such as extrusion velocity and extrusion force. Both the higher extrusion velocity and lower extrusion force will reduce the power and energy conversion efficiency. An optimal combination of extrusion velocity and pressure can achieve the lowest energy consumption per unit product.

A New Plan-Scoring Method Using Normal Tissue Complication Probability for Personalized Treatment Plan Decisions in Prostate Cancer

김광현,이석,심장보,양대식,윤원섭,박영제,김철용,Yuanjie Cao,장경환 한국물리학회 2018 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.72 No.2

The aim of this study was to derive a new plan-scoring index using normal tissue complication probabilities to verify different plans in the selection of personalized treatment. Plans for 12 patients treated with tomotherapy were used to compare scoring for ranking. Dosimetric and biological indexes were analyzed for the plans for a clearly distinguishable group (n = 7) and a similar group (n = 12), using treatment plan verification software that we developed. The quality factor (QF) of our support software for treatment decisions was consistent with the final treatment plan for the clearly distinguishable group (average QF = 1.202, 100% match rate, n = 7) and the similar group (average QF = 1.058, 33% match rate, n = 12). Therefore, we propose a normal tissue complication probability (NTCP) based on the plan scoring index for verification of different plans for personalized treatment-plan selection. Scoring using the new QF showed a 100% match rate (average NTCP QF = 1.0420). The NTCP-based new QF scoring method was adequate for obtaining biological verification quality and organ risk saving using the treatment-planning decision-support software we developed for prostate cancer.

Development of a Web-Based Radiation Toxicity Prediction System Using Metarule-Guided Mining to Predict Radiation Pneumonitis and Esophagitis in Lung Cancer Patients

김광현,이석,주은빈,심장보,양대식,윤원섭,박영제,이남권,김철용,장경환,조광환,Yuanjie Cao 한국물리학회 2019 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.75 No.4

Radiation toxicity grades must be reviewed based on existing knowledge-based clinical evidence or be assessed by referencing the clinical research literature to minimize radiation toxicity associated with radiotherapy. The aim of this study was to develop a radiation toxicity prediction system using metarule-guided mining of the clinical research literature to predict radiation pneumonitis and esophagitis in lung cancer patients. A semantic pattern database was built using 100 clinical research articles. Semantic patterns of prognostic factors and toxicity grades were extracted by metarule-guided mining. Feature analysis and correlation investigation of prognostic factors and toxicity grades were performed by using dendrogram and heatmap. A web-based user interface for the prediction system was designed. Patient prognostic factors were used in this prediction system to predict toxicity grade results. Radiation toxicity grades for patients with radiation pneumonitis and esophagitis were calculated through our prediction system. Age and chemotherapy were prognostic factors as were toxicity grades 1--3 and 5 based on the metarule-guided mining system. The odds ratios had similar trends to those in the existing meta-analysis literature. The radiation toxicity prediction system that we developed can potentially be used as a clinical decision support system for patient-specific radiation treatment after weighting of prognostic factors, performing a correlation analysis, and performing a validity evaluation.

A Text-Based Data Mining and Toxicity Prediction Modeling System for a Clinical Decision Support in Radiation Oncology: A Preliminary Study

김광현,이석,심장보,장경환,양대식,윤원섭,박영지,김철영,Yuanjie Cao 한국물리학회 2017 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.71 No.4

The aim of this study is an integrated research for text-based data mining and toxicity prediction modeling system for clinical decision support system based on big data in radiation oncology as a preliminary research. The structured and unstructured data were prepared by treatment plans and the unstructured data were extracted by dose-volume data image pattern recognition of prostate cancer for research articles crawling through the internet. We modeled an artificial neural network to build a predictor model system for toxicity prediction of organs at risk. We used a text-based data mining approach to build the artificial neural network model for bladder and rectum complication predictions. The pattern recognition method was used to mine the unstructured toxicity data for dose-volume at the detection accuracy of 97.9%. The confusion matrix and training model of the neural network were achieved with 50 modeled plans (n = 50) for validation. The toxicity level was analyzed and the risk factors for 25% bladder, 50% bladder, 20% rectum, and 50% rectum were calculated by the artificial neural network algorithm. As a result, 32 plans could cause complication but 18 plans were designed as non-complication among 50 modeled plans. We integrated data mining and a toxicity modeling method for toxicity prediction using prostate cancer cases. It is shown that a preprocessing analysis using text-based data mining and prediction modeling can be expanded to personalized patient treatment decision support based on big data.

Evaluation of the Dosimetric Accuracy for a Couch-Based Tracking System (CBTS)

Kyung Hwan Chang,Suk Lee,Kwang Hyeon Kim,Jang Bo Shim,Dae Sik Yang,Young Je Park,Won Sup Yoon,Chul Yong Kim,Yuanjie Cao 한국물리학회 2016 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.69 No.2

In this study, the geometric and dosimetric accuracy of an in-house-developed couch-based tracking system (CBTS) was investigated using both film and in-house-developed polymer gel dosimeters. We evaluated the 1D and the 2D motion accuracies of our couch system by using Gafchromic EBT film. For the 1D test, the couch system was moved 5, 10, and 20 mm in the X, Y, and Z directions, respectively. Meanwhile, for the 2D test, it was moved along the XY, YZ, and ZX directions. We compared the profiles, full widths at half maximum (FWHMs), and penumbras between the static and the tracking fields. For the 3D test, we quantitatively compared the dose distribution between the static and the tracking fields by using the polymer gel dosimeter when it was simultaneously moved in the XYZ directions. We confirmed that the film was moved according to motion amplitudes of 5, 10, and 20 mm in the X, Y, and Z directions, respectively, in the 1D and 2D motion tests. The value of the FWHM of the static field and the three tracking fields were 51.88, 53.28, 57.67, and 64.43 mm, respectively. Two types of penumbras became wider with increasing amplitudes compared to the static field. For the 3D test, the dose distribution of the XYZ tracking field was qualitatively larger than that of the static field. We conclude that this CBTS has the potential for pre-clinical applications in adaptive radiation therapy.

Basic Radiological Characteristics of a Non-Scattering Gel Dosimeter for 3D Dosimetry

Kyung Hwan Chang,Yunseo Ji,Suk Lee,Kwang Hyeon Kim,Dae Sik Yang,Jung Ae Lee,Young Je Park,Won Sup Yoon,Chul Yong Kim,Yuanjie Cao,Samju Cho 한국물리학회 2016 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.69 No.11

We used a spectrophotometer to compare the dosimetric properties of two non-scattering (radiochromic) gel dosimeters: a non-scattering gel dosimeter developed in-house and a PRESAGETM gel dosimeter. We evaluated the dosimetric characteristics, including spectral absorption, dose linearity, reproducibility, and dose rate dependency of the two gel dosimeters. The non-scattering gel and the PRESAGETM gel dosimeters showed peak sensitivity at wavelengths of 600 nm and 630 nm, respectively. Over a range of doses the best dose linearities of the non-scattering and the PRESAGETM gel dosimeters resulted in R2 values of 0.99 at wavelengths of 600 nm and 630 nm, respectively. The reproducibility and dose-rate dependence of each of the two gel dosimeters were within the range of ±3 %. Our results revealed that the peak sensitivities of the two radiochromic gel dosimeters were significantly different; the in-house non-scattering gel dosimeter demonstrated peak sensitivity at a wavelength of 600 nm while the PRESAGETM gel dosimeter had peak sensitivity at a wavelength of 630 nm. We confirmed that for 3D gel dosimetry, the in-house non-scattering gel dosimeter had a more stable dose response compared with a commercial non-scattering gel dosimeter.