Investigation on the temperature distribution and strength of flat steel ribbon wound cryogenic high-pressure vessel

By analyzing heat transfer on the wall of fiat steel ribbon wound vessel （FSRWV）, a numerical model of temperature distribution on the entire wall （including inner core wall, flat steel ribbons, outside cylinder of jacket and insulating layer） was established by the authors. With the model, the temperature distribution and the length change in the vessel walls and flat steel ribbons in low temperature are calculated and analyzed. The results show that the flat steel ribbon wound cryogenic high-pressure vessel is simpler in structure, safer and easier to manufacture than those of conventional ones.

Evaluation on Safety and Reliability of High-Pressure Vessel in Missile System

Through theoretical analysis of reliability and simulation analysis of dispersivi of d a/ d N based on Monte Carlo method, the distribution function of n and c was set up. Meanwhile, the distribution of critical opening displacement(COD)δ c was defined by the use of coherent coefficient method, and the probabilistic model of defects assessment of military special vessel was built. Thereby the theoretical and practical fundamental research on evaluation of reliability of military high pressure vessels was carried out.

Influence of introducing Zr,Ti,Nb and Ce elements on externally solidified crystals and mechanical properties of high-pressure die-casting Al–Si alloy

High pressure die casting(HPDC)AlSi10Mn Mg alloy castings are widely used in the automobile industry.Mg can optimize the mechanical properties of castings through heat treatment,while the release of thermal stress arouses the deformation of large integrated die-castings.Herein,the development of non-heat treatment Al alloys is becoming the hot topic.In addition,HPDC contains externally solidified crystals(ESCs),which are detrimental to the mechanical properties of castings.To achieve high strength and toughness of non-heat treatment die-casting Al-Si alloy,we used AlSi9Mn alloy as matrix with the introduction of Zr,Ti,Nb,and Ce.Their influences on ESCs and mechanical properties were systematically investigated through three-dimensional reconstruction and thermodynamic simulation.Our results reveal that the addition of Ti increased ESCs'size and porosity,while the introduction of Nb refined ESCs and decreased porosity.Meanwhile,large-sized Al_3(Zr,Ti)phases formed and degraded the mechanical properties.Subsequent introduction of Ce resulted in the poisoning effect and reduced mechanical properties.

Nano-scale Reinforcements and Properties of Al-Si-Cu Alloy Processed by High-Pressure Torsion

To improve the comprehensive mechanical properties of Al-Si-Cu alloy,it was treated by a high-pressure torsion process,and the effect of the deformation degree on the microstructure and properties of the Al-Si-Cu alloy was studied.The results show that the reinforcements(β-Si andθ-CuAl_(2)phases)of the Al-Si-Cu alloy are dispersed in theα-Al matrix phase with finer phase size after the treatment.The processed samples exhibit grain sizes in the submicron or even nanometer range,which effectively improves the mechanical properties of the material.The hardness and strength of the deformed alloy are both significantly raised to 268 HV and 390.04 MPa by 10 turns HPT process,and the fracture morphology shows that the material gradually transits from brittle to plastic before and after deformation.The elements interdiffusion at the interface between the phases has also been effectively enhanced.In addition,it is found that the severe plastic deformation at room temperature induces a ternary eutectic reaction,resulting in the formation of ternary Al+Si+CuAl_(2)eutectic.

Experimental and Finite Element Analysis of Corroded High-Pressure Pipeline Repaired by Laminated Composite

Repairs of corroded high-pressure pipelines are essential for fluids transportation under high pressure.One of the methods used in their repairs is the use of layered composites.The composite used must have the necessary strength.Therefore,the experiments and analytical solutions presented in this paper are performed according to the relevant standards and codes,including ASME PCC-2,ASME B31.8S,ASME B31.4,ISO 24817 and ASME B31.G.In addition,the experimental tests are replicated numerically using the finite element method.Setting the strain gauges at different distances from the defect location,can reduce the nonlinear effects,deformation,and fluctuations due to the high pressure.The direct relationship between the depth of an axial defect and the stress concentration is observed at the inner side edges of the defect.Composite reparation reduces the non-linearities related to the sharp variation of the geometry and a more reliable numerical simulation could be performed.

Numerical Simulation Analysis of the Transformer Fire Extinguishing Process with a High-Pressure Water Mist System under Different Conditions

To thoroughly study the extinguishing effect of a high-pressure water mist fire extinguishing system when a transformer fire occurs,a 3D experimental model of a transformer is established in this work by employing Fire Dynamics Simulator(FDS)software.More specifically,by setting different parameters,the process of the highpressure water mist fire extinguishing system with the presence of both diverse ambient temperatures and water mist sprinkler laying conditions is simulated.In addition,the fire extinguishing effect of the employed high-pressure water mist system with the implementation of different strategies is systematically analyzed.The extracted results show that a fire source farther away fromthe centerline leads to a lower local temperature distribution.In addition,as the ambient temperature increases,the temperature above the fire source decreases,while the temperature and the concentrationof theupperflue gas layer bothdecrease.Interestingly,after thehigh-pressurewatermist sprinkler begins to operate,both the temperature distribution above the fire source and the concentration of the flue gas decrease,which indicates that the high-pressure water mist system plays the role of cooling and dust removal.By comparing various sprinkler laying methods,it is found that the lower sprinkler height has a better effect on the temperature above the fire source,the temperature of the upper flue gas layer,and the concentration of the flue gas.Moreover,when the sprinkler is spread over thewhole transformer,the cooling effect on both the temperature above the fire source and the temperature of the upper flue gas layer is good,whereas the change in the concentration of the flue gas above the fire source is not obvious compared to the case where the sprinkler is not fully spread.

The discovery of TiO_(2)-Ⅱ,the α-PbO_(2)-structured high-pressure polymorph of rutile,in the Suizhou L6 chondrite

We report the discovery of TiO_(2)-Ⅱ in the unmelted rock of the shocked Suizhou L6 chondrite.Natural TiO_(2)-Ⅱ was previously found in ultrahigh-pressure metamorphic and mantle-derived rocks,terrestrial impact structures,and tektite.Our microscopic,Raman spectroscopic,electron microprobe and transmission electron microscopic investigations have revealed:(1) All observed TiO_(2)-Ⅱ grains are related with ilmenite and pyrophanite;(2) TiO_(2)-Ⅱ occurs as needle-and leaf-shaped inclusions in llmenite and patch-,tape-shaped body in pyrophanite;(3)The composition of TiO_(2)-Ⅱ is identical with that of its precursor rutile;(4) The Raman spectrum of TiO_(2)-Ⅱ is in good agreement with that of natural and synthesized α-PbO_(2)-type TiO_(2);(5) TiO_(2)-Ⅱ occurs mainly in the form of well-ordered nano-domains and small mis-orientation among the domains can be observed.(6) All electron diffraction reflections from TiO_(2)-Ⅱ can be indexed to α-PbO_(2)structure in space group Pbcn with lattice parameters of a=4.481 ?,b=5.578 A and c=4.921 A;(7) The exsolution inclusions of rutile from host ilmenite are mostly connected with an alternation process along the lamellar twinning plane of ilmenite induced by shockinduced high pressure and high temperature;(8) The P-T regime of 20-25 GPa and 1000 ℃ estimated for the Suizhou unmelted rock is suitable for phase transition of rutile into TiO_(2)-Ⅱ phase.

A new transition metal diphosphideα-MoP_(2) synthesized by a high-temperature and high-pressure technique

Monoclinicα-MoP_(2),with the OsGe2-type structure(space group C2/m,Z=4)and lattice parameters a=8.7248(11)Å,b=3.2322(4)Å,c=7.4724(9)Å,andβ=119.263°,was synthesized under a pressure of 4~GPa at a temperature between 1100℃and 1200℃.The structure ofα-MoP_(2) and its relationship to other transition metal diphosphides are discussed.Surprisingly,the ambient pressure phase orthorhombicβ-MoP_(2)(space group Cmc21)is denser in structure thanα-MoP_(2).Room-temperature high-pressure x-ray diffraction studies exclude the possibility of phase transition fromβ-MoP_(2) to α-MoP_(2),suggesting thatα-MoP_(2) is a stable phase at ambient conditions;this is also supported by the total energy and phonon calculations.

Blood-brain barrier pathology in cerebral small vessel disease

Cerebral small vessel disease is a neurological disease that affects the brain microvasculature and which is commonly observed among the elderly.Although at first it was considered innocuous,small vessel disease is nowadays regarded as one of the major vascular causes of dementia.Radiological signs of small vessel disease include small subcortical infarcts,white matter magnetic resonance imaging hyperintensities,lacunes,enlarged perivascular spaces,cerebral microbleeds,and brain atrophy;however,great heterogeneity in clinical symptoms is observed in small vessel disease patients.The pathophysiology of these lesions has been linked to multiple processes,such as hypoperfusion,defective cerebrovascular reactivity,and blood-brain barrier dysfunction.Notably,studies on small vessel disease suggest that blood-brain barrier dysfunction is among the earliest mechanisms in small vessel disease and might contribute to the development of the hallmarks of small vessel disease.Therefore,the purpose of this review is to provide a new foundation in the study of small vessel disease pathology.First,we discuss the main structural domains and functions of the blood-brain barrier.Secondly,we review the most recent evidence on blood-brain barrier dysfunction linked to small vessel disease.Finally,we conclude with a discussion on future perspectives and propose potential treatment targets and interventions.

High-pressure new phases of V–N compounds

The high-pressure diagram of V–N compounds is enriched by proposed seven new stable high-pressure phases.The P-1-VN_4with the armchair N-rich structure may be quenched to ambient conditions.The formed N–N covalent bond plays an important role for the structural stability of N-chain.The charge transfer results in a V–N ionic bond interaction,which further improves the stability of N-chain structure.The P-1-VN_4,P4mnc-VN_8,and Immm-VN_(10)with the outstanding detonation properties have potential application in explosive field.

Cognitive impairment in cerebral small vessel disease induced by hypertension

Hypertension is a primary risk factor for the progression of cognitive impairment caused by cerebral small vessel disease,the most common cerebrovascular disease.Howeve r,the causal relationship between hypertension and cerebral small vessel disease remains unclear.Hypertension has substantial negative impacts on brain health and is recognized as a risk factor for cerebrovascular disease.Chronic hypertension and lifestyle factors are associated with risks for stro ke and dementia,and cerebral small vessel disease can cause dementia and stroke.Hypertension is the main driver of cerebral small vessel disease,which changes the structure and function of cerebral vessels via various mechanisms and leads to lacunar infarction,leukoaraiosis,white matter lesions,and intracerebral hemorrhage,ultimately res ulting in cognitive decline and demonstrating that the brain is the to rget organ of hypertension.This review updates our understanding of the pathogenesis of hypertensioninduced cerebral small vessel disease and the res ulting changes in brain structure and function and declines in cognitive ability.We also discuss drugs to treat cerebral small vessel disease and cognitive impairment.

An Efficient Long Short-Term Memory and Gated Recurrent Unit Based Smart Vessel Trajectory Prediction Using Automatic Identification System Data

Maritime transportation,a cornerstone of global trade,faces increasing safety challenges due to growing sea traffic volumes.This study proposes a novel approach to vessel trajectory prediction utilizing Automatic Identification System(AIS)data and advanced deep learning models,including Long Short-Term Memory(LSTM),Gated Recurrent Unit(GRU),Bidirectional LSTM(DBLSTM),Simple Recurrent Neural Network(SimpleRNN),and Kalman Filtering.The research implemented rigorous AIS data preprocessing,encompassing record deduplication,noise elimination,stationary simplification,and removal of insignificant trajectories.Models were trained using key navigational parameters:latitude,longitude,speed,and heading.Spatiotemporal aware processing through trajectory segmentation and topological data analysis(TDA)was employed to capture dynamic patterns.Validation using a three-month AIS dataset demonstrated significant improvements in prediction accuracy.The GRU model exhibited superior performance,achieving training losses of 0.0020(Mean Squared Error,MSE)and 0.0334(Mean Absolute Error,MAE),with validation losses of 0.0708(MSE)and 0.1720(MAE).The LSTM model showed comparable efficacy,with training losses of 0.0011(MSE)and 0.0258(MAE),and validation losses of 0.2290(MSE)and 0.2652(MAE).Both models demonstrated reductions in training and validation losses,measured by MAE,MSE,Average Displacement Error(ADE),and Final Displacement Error(FDE).This research underscores the potential of advanced deep learning models in enhancing maritime safety through more accurate trajectory predictions,contributing significantly to the development of robust,intelligent navigation systems for the maritime industry.

An Implementation of Multiscale Line Detection and Mathematical Morphology for Efficient and Precise Blood Vessel Segmentation in Fundus Images

Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood vessels.The task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different pathologies.Furthermore,the speed of the retinal vessel segmentation system is of utmost importance.With the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the algorithm.To address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical morphology.Our algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)dataset.The experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE datasets.Notably,our algorithmexhibits competitive performance with state-of-the-art methods.Importantly,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE datasets.It is worth noting that these results were achieved using Matlab scripts containing multiple loops.This suggests that the processing time can be further reduced by replacing loops with vectorization.Thus the proposed algorithm can be deployed in real time applications.In summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.

Vulnerability and Conservation of Nearshore Cetaceans to Increasing Vessel Traffic:The Indo-Pacific Humpback Dolphin in the South China Sea

A comprehensive risk assessment to evaluate the vulnerability of the nearshore cetaceans to increasing marine traffic is lacking.In this study,the risk to Indo-Pacific humpback dolphins(Sousa chinensis)in the main habitats in China was assessed based on a semiquantitative spatial vulnerability analysis.85%of the(sub)population which overlapped with the lanes of ferries and/or cargo vessels,with exposure scores of 1.23±0.31(calculated based on the proportion of sea routes that overlap the dolphin’s range).A combination of high exposure to the sea routes and sensitivity to marine traffic would render the(sub)populations to be highly vulnerable(EPRE:5.21 and XM:4.47).A low frequency of vessels and an awareness of the ecology assures a low vulnerability(SH:2.43,EZ:2.73).Uncertainty scores were commonly lower for the higher vulnerable populations,and higher for the lower vulnerable populations,suggesting additional field data and more monitoring are necessary.Six years of field data have been used to analyze the influences of various types of marine traffic on humpback dolphin behavior.Fishing and non-fishing vessels were significantly different(χ^(2)=65.19,p<0.01).The humpback dolphins were attracted by fishing vessels(83.1%)but avoided non-fishing vessels(95.2%).We recommend a management with seasonal and geographical constraints,to balance economic development and environmental conservation.

Experimental and numerical study of hypervelocity impact damage on composite overwrapped pressure vessels

Ground-based tests are important for studying hypervelocity impact(HVI)damage to spacecraft pressure vessels in the orbital debris environment.We analyzed the damage to composite overwrapped pressure vessels(COPVs)in the HVI tests and classified the damage into non-catastrophic damage and catastrophic damage.We proposed a numerical simulation method to further study non-catastrophic damage and revealed the characteristics and mechanisms of non-catastrophic damage affected by impact conditions and internal pressures.The fragments of the catastrophically damaged COPVs were collected after the tests.The crack distribution and propagation process of the catastrophic ruptures of the COPVs were analyzed.Our findings contribute to understanding the damage characteristics and mechanisms of COPVs by HVIs.

Meningeal lymphatic vessel crosstalk with central nervous system immune cells in aging and neurodegenerative diseases

Meningeal lymphatic vessels form a relationship between the nervous system and periphery, which is relevant in both health and disease. Meningeal lymphatic vessels not only play a key role in the drainage of brain metabolites but also contribute to antigen delivery and immune cell activation. The advent of novel genomic technologies has enabled rapid progress in the characterization of myeloid and lymphoid cells and their interactions with meningeal lymphatic vessels within the central nervous system. In this review, we provide an overview of the multifaceted roles of meningeal lymphatic vessels within the context of the central nervous system immune network, highlighting recent discoveries on the immunological niche provided by meningeal lymphatic vessels. Furthermore, we delve into the mechanisms of crosstalk between meningeal lymphatic vessels and immune cells in the central nervous system under both homeostatic conditions and neurodegenerative diseases, discussing how these interactions shape the pathological outcomes. Regulation of meningeal lymphatic vessel function and structure can influence lymphatic drainage, cerebrospinal fluid-borne immune modulators, and immune cell populations in aging and neurodegenerative disorders, thereby playing a key role in shaping meningeal and brain parenchyma immunity.

A Deformable Network with Attention Mechanism for Retinal Vessel Segmentation

The intensive application of deep learning in medical image processing has facilitated the advancement of automatic retinal vessel segmentation research.To overcome the limitation that traditional U-shaped vessel segmentation networks fail to extract features in fundus image sufficiently,we propose a novel network(DSeU-net)based on deformable convolution and squeeze excitation residual module.The deformable convolution is utilized to dynamically adjust the receptive field for the feature extraction of retinal vessel.And the squeeze excitation residual module is used to scale the weights of the low-level features so that the network learns the complex relationships of the different feature layers efficiently.We validate the DSeU-net on three public retinal vessel segmentation datasets including DRIVE,CHASEDB1,and STARE,and the experimental results demonstrate the satisfactory segmentation performance of the network.

Repeatability,interocular correlation and agreement of optic nerve head vessel density in healthy eyes:a sweptsource optical coherence tomographic angiography study

AIM:To assess the repeatability,interocular correlation,and agreement of quantitative swept-source optical coherence tomography angiography(OCTA)optic nerve head(ONH)parameters in healthy subjects.METHODS:Thir ty-three healthy subjects were enrolled.The ONH of both eyes were imaged four times by a swept-source-OCTA using a 3 mm×3 mm scanning protocol.Images of the radial peripapillary capillary were analyzed by a customized Matlab program,and the vessel density,fractal dimension,and vessel diameter index were measured.The repeatability of the four scans was determined by the intraclass correlation coefficient(ICC).The most well-centered optic disc from the four repeated scans was then selected for the interocular correlation and agreement analysis using the Pearson correlation coefficient,ICC and Bland-Altman plots.RESULTS:All swept-source-OCTA ONH parameters exhibited certain repeatability,with ICC>0.760 and coefficient of variation(CoV)≤7.301%.The obvious interocular correlation was observed for papillary vessel density(ICC=0.857),vessel diameter index(ICC=0.857)and fractal dimension(ICC=0.906),while circumpapillary vessel density exhibited moderate interocular correlation(ICC=0.687).Bland-Altman plots revealed an agreement range of-5.26%to 6.21%for circumpapillary vessel density.CONCLUSION:OCTA ONH parameters demonstrate good repeatability in healthy subjects.The interocular correlations of papillary vessel density,fractal dimension and vessel diameter index are high,but the correlation for circumpapillary vessel density is moderate.

Clinical Value of the Quantitative Flow Ratio to Predict Long-term Target Vessel Failure in Patients with In-stent Restenosis after Drug-coated Balloon Angioplasty

Objective The study sought to investigate the clinical predictive value of quantitative flow ratio(QFR)for the long-term target vessel failure(TVF)outcome in patients with in-stent restenosis(ISR)by using drug-coated balloon(DCB)treatment after a long-term follow-up.Methods This was a retrospective study.A total of 186 patients who underwent DCB angioplasty for ISR in two hospitals from March 2014 to September 2019 were enrolled.The QFR of the entire target vessel was measured offline.The primary endpoint was TVF,including target vessel-cardiac death(TV-CD),target vessel-myocardial infarction(TV-MI),and clinically driven-target vessel revascularization(CD-TVR).Results The follow-up time was 3.09±1.53 years,and 50 patients had TVF.The QFR immediately after percutaneous coronary intervention(PCI)was significantly lower in the TVF group than in the no-TVF group.Multivariable Cox regression analysis indicated that the QFR immediately after PCI was an excellent predictor for TVF after the long-term follow-up[hazard ratio(HR):5.15×10−5(6.13×10−8−0.043);P<0.01].Receiver-operating characteristic(ROC)curve analysis demonstrated that the optimal cut-off value of the QFR immediately after PCI for predicting the long-term TVF was 0.925(area under the curve:0.886,95%confidence interval:0.834–0.938;sensitivity:83.40%,specificity:88.00;P<0.01).In addition,QFR≤0.925 post-PCI was strongly correlated with the TVF,including TV-MI and CD-TVR(P<0.01).Conclusion The QFR immediately after PCI showed a high predictive value of TVF after a long-term follow-up in ISR patients who underwent DCB angioplasty.A lower QFR immediately after PCI was associated with a worse TVF outcome.

Machine Learning for Selecting Important Clinical Markers of Imaging Subgroups of Cerebral Small Vessel DiseaseBased on a Common Data Model

Differences in the imaging subgroups of cerebral small vessel disease(CSVD)need to be further explored.First,we use propensity score matching to obtain balanced datasets.Then random forest(RF)is adopted to classify the subgroups compared with support vector machine(SVM)and extreme gradient boosting(XGBoost),and to select the features.The top 10 important features are included in the stepwise logistic regression,and the odds ratio(OR)and 95%confidence interval(CI)are obtained.There are 41290 adult inpatient records diagnosed with CSVD.Accuracy and area under curve(AUC)of RF are close to 0.7,which performs best in classification compared to SVM and XGBoost.OR and 95%CI of hematocrit for white matter lesions(WMLs),lacunes,microbleeds,atrophy,and enlarged perivascular space(EPVS)are 0.9875(0.9857−0.9893),0.9728(0.9705−0.9752),0.9782(0.9740−0.9824),1.0093(1.0081−1.0106),and 0.9716(0.9597−0.9832).OR and 95%CI of red cell distribution width for WMLs,lacunes,atrophy,and EPVS are 0.9600(0.9538−0.9662),0.9630(0.9559−0.9702),1.0751(1.0686−1.0817),and 0.9304(0.8864−0.9755).OR and 95%CI of platelet distribution width for WMLs,lacunes,and microbleeds are 1.1796(1.1636−1.1958),1.1663(1.1476−1.1853),and 1.0416(1.0152−1.0687).This study proposes a new analytical framework to select important clinical markers for CSVD with machine learning based on a common data model,which has low cost,fast speed,large sample size,and continuous data sources.