A regenerative supercritical-subcritical dual-loop organic Rankine cycle system for energy recovery from the waste heat of internal combustion engines

Organic Rankine cycle (ORC) system is considered as a promising technology for energy recovery from the waste heat rejected by internal combustion (IC) engines. However, such waste heat is normally contained in both coolant and exhaust gases at quite different temperatures. A single ORC system is usually unable to efficiently recover energy from both of these waste heat sources. A dual loop ORC system which essentially has two cascaded ORCs to recover energy from the engine’s exhaust gases and coolant separately has been proposed to address this challenge. In this way, the overall efficiency of energy recovery can be substantially improved. This paper examines a regenerative dual loop ORC system using a pair of environmentally friendly refrigerants, R1233zd and R1234yf, as working fluids, to recover energy from the waste heat of a compressed natural gas (CNG) engine. Unlike most previous studies focusing on the ORC system only, the present research analyses the ORC system and CNG engine together as an integrated system. As such, the ORC system is analysed on the basis of real data of waste heat sources of the CNG engine under various operational conditions. A numerical model is employed to analyse the performances of the proposed dual loop cycle with four pairs of working fluids. The effects of a regenerative heat exchanger and several other key operating parameters are also analysed and discussed in detail. The performance of the integrated engine-ORC system is then analysed under actual engine operating conditions which were measured beforehand. The performance of the proposed system under off-design conditions has also been analysed. The obtained results show that the proposed dual loop ORC system could achieve better performance than other ORC systems for similar applications

Parametric optimization and heat transfer analysis of a dual loop ORC (organic Rankine cycle) system for CNG engine waste heat recovery

In this study, a dual loop ORC (organic Rankine cycle) system is adopted to recover exhaust energy, waste heat from the coolant system, and intercooler heat rejection of a six-cylinder CNG (compressed natural gas) engine. The thermodynamic, heat transfer, and optimization models for the dual loop ORC system are established. On the basis of the waste heat characteristics of the CNG engine over the whole operating range, a GA (genetic algorithm) is used to solve the Pareto solution for the thermodynamic and heat transfer performances to maximize net power output and minimize heat transfer area. Combined with optimization results, the optimal parameter regions of the dual loop ORC system are determined under various operating conditions. Then, the variation in the heat transfer area with the operating conditions of the CNG engine is analyzed. The results show that the optimal evaporation pressure and superheat degree of the HT (high temperature) cycle are mainly influenced by the operating conditions of the CNG engine. The optimal evaporation pressure and superheat degree of the HT cycle over the whole operating range are within 2.5–2.9 MPa and 0.43–12.35 K, respectively. The optimal condensation temperature of the HT cycle, evaporation and condensation temperatures of the LT (low temperature) cycle, and exhaust temperature at the outlet of evaporator 1 are kept nearly constant under various operating conditions of the CNG engine. The thermal efficiency of the dual loop ORC system is within the range of 8.79%–10.17%. The dual loop ORC system achieves the maximum net power output of 23.62 kW under the engine rated condition. In addition, the operating conditions of the CNG engine and the operating parameters of the dual loop ORC system significantly influence the heat transfer areas for each heat exchanger

Thermodynamic analysis of a dual-loop organic Rankine cycle (ORC) for waste heat recovery of a petrol engine

Huge amounts of low-grade heat energy are discharged to the environment by vehicular engines. Considering the large number of vehicles in the world, such waste energy has a great impact on our environment globally. The Organic Rankine Cycle (ORC), which uses an organic fluid with a low boiling point as the working medium, is considered to be the most promising technology to recover energy from low-grade waste heat. In this study, a dual-loop ORC is presented to simultaneously recover energy from both the exhaust gases and the coolant of a petrol engine. A high-temperature (HT) ORC loop is used to recover heat from the exhaust gases, while a low-temperature (LT) ORC loop is used to recover heat from the coolant and the condensation heat of the HT loop. Figure 1 shows the schematic of the dual-loop ORC. Differing from previous research, two more environmentally friendly working fluids are used, and the corresponding optimisation is conducted. First, the system structure and operating principle are described. Then, a mathematical model of the designed dual-loop ORC is established. Next, the performance of the dual-loop cycle is analysed over the entire engine operating region. Furthermore, the states of each point along the cycle and the heat load of each component are compared with the results of previous research. The results show that the dual-loop ORC can effectively recover the waste heat from the petrol engine, and that the effective thermal efficiency can be improved by about 20 ~ 24%, 14~20%, and 30% in the high-speed, medium-speed, and low-speed operation regions, respectively. The designed dual-loop ORC can achieve a higher system efficiency than previous ORCs of this structure. Therefore, it is a good choice for waste heat recovery from vehicle engines

Advance in integrating platinum-based chemotherapy with radiotherapy for locally advanced nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a malignant tumor characterized by the malignant transformation of nasopharyngeal epithelial cells. It is highly sensitive to radiation therapy, making radiotherapy the primary treatment modality. However, 60-80% of patients are initially diagnosed with locally advanced NPC (LA-NPC), where radiotherapy alone often fails to achieve desirable outcomes. Therefore, combining radiotherapy with chemotherapy has emerged as an effective strategy to optimize treatment for LA-NPC patients. Among the various chemotherapy regimens, concurrent chemoradiotherapy (CCRT) using platinum-based drugs has been established as the most commonly utilized approach for LA-NPC patients. The extensive utilization of platinum drugs in clinical settings underscores their therapeutic potential and emphasizes ongoing efforts in the development of novel platinum-based complexes for anticancer therapy. The aim of this review is to elucidate the remarkable advances made in the field of platinum-based therapies for nasopharyngeal carcinoma, emphasizing their transformative impact on patient prognosis

Interval Type-2 Fuzzy Programming Method for Risky Multicriteria Decision-Making with Heterogeneous Relationship

We propose a new interval type-2 fuzzy (IT2F) programming method for risky multicriteria decision-making (MCDM) problems with IT2F truth degrees, where the criteria exhibit a heterogeneous relationship and decision-makers behave according to bounded rationality. First, we develop a technique to calculate the Banzhaf-based overall perceived utility values of alternatives based on 2-additive fuzzy measures and regret theory. Subsequently, considering pairwise comparisons of alternatives with IT2F truth degrees, we define the Banzhaf-based IT2F risky consistency index (BIT2FRCI) and the Banzhaf-based IT2F risky inconsistency index (BIT2FRII). Next, to identify the optimal weights, an IT2F programming model is established based on the concept that BIT2FRII must be minimized and must not exceed the BIT2FRCI using a fixed IT2F set. Furthermore, we design an effective algorithm using an external archive-based constrained state transition algorithm to solve the established model. Accordingly, the ranking order of alternatives is derived using the Banzhaf-based overall perceived utility values. Experimental studies pertaining to investment selection problems demonstrate the state-of-the-art performance of the proposed method, that is, its strong capability in addressing risky MCDM problems

T cell senescence: a new perspective on immunotherapy in lung cancer

T cell senescence is an indication of T cell dysfunction. The ability of senescent T cells to respond to cognate antigens is reduced and they are in the late stage of differentiation and proliferation; therefore, they cannot recognize and eliminate tumor cells in a timely and effective manner, leading to the formation of the suppressive tumor microenvironment. Establishing methods to reverse T cell senescence is particularly important for immunotherapy. Aging exacerbates profound changes in the immune system, leading to increased susceptibility to chronic, infectious, and autoimmune diseases. Patients with malignant lung tumors have impaired immune function with a high risk of recurrence, metastasis, and mortality. Immunotherapy based on PD-1, PD-L1, CTLA-4, and other immune checkpoints is promising for treating lung malignancies. However, T cell senescence can lead to low efficacy or unsuccessful treatment results in some immunotherapies. Efficiently blocking and reversing T cell senescence is a key goal of the enhancement of tumor immunotherapy. This study discusses the characteristics, mechanism, and expression of T cell senescence in malignant lung tumors and the treatment strategies

Association between diabetes at different diagnostic ages and risk of cancer incidence and mortality: a cohort study

BackgroundDifferent ages for diagnosis of diabetes have diverse effects on risks of cardiovascular disease, dementia, and mortality, but there is little evidence of cancer. This study investigated the relationship between diabetes at different diagnostic ages and risks of cancer incidence and mortality in people aged 37–73 years.MethodsParticipants with diabetes in the UK Biobank prospective cohort were divided into four groups: ≤40, 41–50, 51–60, and >60 years according to age at diagnosis. A total of 26,318 diabetics and 105,272 controls (1:4 randomly selected for each diabetic matched by the same baseline age) were included. We calculated the incidence density, standardized incidence, and mortality rates of cancer. Cox proportional hazard model was used to examine the associations of diabetes at different diagnostic ages with cancer incidence and mortality, followed by subgroup analyses.ResultsCompared to corresponding controls, standardized incidence and mortality rates of overall and digestive system cancers were higher in diabetes diagnosed at age 41–50, 51–60, and >60 years, especially at 51–60 years. Individuals diagnosed with diabetes at different ages were at higher risk to develop site-specific cancers, with a prominently increased risk of liver cancer since the diagnosis age of >40 years. Significantly, participants with diabetes diagnosed at 51–60 years were correlated with various site-specific cancer risks [hazard ratio (HR) for incidence: 1.088–2.416, HR for mortality: 1.276–3.269]. Moreover, for mortality of digestive system cancers, we observed an interaction effect between smoking and diabetes diagnosed at 51–60 years.ConclusionOur findings highlighted that the age at diagnosis of diabetes, especially 51–60 years, was critical risks of cancer incidence and mortality and may represent a potential preventative window for cancer

Development and external validation of dual online tools for prognostic assessment in elderly patients with high-grade glioma: a comprehensive study using SEER and Chinese cohorts

BackgroundElderly individuals diagnosed with high-grade gliomas frequently experience unfavorable outcomes. We aimed to design two web-based instruments for prognosis to predict overall survival (OS) and cancer-specific survival (CSS), assisting clinical decision-making.MethodsWe scrutinized data from the SEER database on 5,245 elderly patients diagnosed with high-grade glioma between 2000-2020, segmenting them into training (3,672) and validation (1,573) subsets. An additional external validation cohort was obtained from our institution. Prognostic determinants were pinpointed using Cox regression analyses, which facilitated the construction of the nomogram. The nomogram’s predictive precision for OS and CSS was gauged using calibration and ROC curves, the C-index, and decision curve analysis (DCA). Based on risk scores, patients were stratified into high or low-risk categories, and survival disparities were explored.ResultsUsing multivariate Cox regression, we identified several prognostic factors for overall survival (OS) and cancer-specific survival (CSS) in elderly patients with high-grade gliomas, including age, tumor location, size, surgical technique, and therapies. Two digital nomograms were formulated anchored on these determinants. For OS, the C-index values in the training, internal, and external validation cohorts were 0.734, 0.729, and 0.701, respectively. We also derived AUC values for 3-, 6-, and 12-month periods. For CSS, the C-index values for the training and validation groups were 0.733 and 0.727, with analogous AUC metrics. The efficacy and clinical relevance of the nomograms were corroborated via ROC curves, calibration plots, and DCA for both cohorts.ConclusionOur investigation pinpointed pivotal risk factors in elderly glioma patients, leading to the development of an instrumental prognostic nomogram for OS and CSS. This instrument offers invaluable insights to optimize treatment strategies