The Design and Numerical Study of a 2MWh Molten Salt Thermocline Tank

AbstractThe two tank molten salt thermal storage system is widely used in the commercialized solar thermal power plant. However, the thermocline storage system with a low-cost filler material is a more economically feasible option. In this study, a transient two-dimensional and two-temperature model is developed to investigate the heat transfer and fluid dynamics in a molten salt thermocline thermal storage system. After model validation, the effects of inlet flow boundary condition and storage medium properties including fluid and solid materials on the thermal performance of thermocline storage system are investigated. The results show that thermoclne thickness increases slowest with solar salt as heat transfer fluid (HTF) and Cofalit® as solid material in the thermocline tank. Any non-uniformity in the inlet velocity flow would only enhance mixing and widen the thermocline appreciably, which contributes to the loss of thermodynamic availability of stored energy. The thermocline thickness increases with the non-uniformity of the inlet velocity boundary condition. So smaller non-uniformity of inlet flow is better in non-uniform flow though it may causes larger fluctuations in average outlet temperature. Smaller inlet mass flow rate is better for the thermocline storage tank, while it also causes smaller discharging power. With the chosen basic design parameters such as fluid and solid materials, the size of a 2MWh thermocline tank is determined by a simple one-dimensional design method. Tank with larger H/D ratio has higher discharge efficiency. It helps to figure out the thermal stratification mechanism of a storage tank and thereby to determine optimum design and operating conditions

High-pressure behaviors of carbon nanotubes

In this paper, we have reviewed the experimental and theoretical studies on pressure-induced polygonization, ovalization, racetrack–shape deformation, and polymerization of carbon nanotubes (CNTs). The corresponding electronic, optical, and mechanical changes accompanying these behaviors have been discussed. The transformations of armchair (n, n) CNT bundles (n = 2, 3, 4, 6, and 8) under hydrostatic or nonhydrostatic pressure into new carbons, including recently proposed superhard bct-C₄, Cco-C₈, and B-B1AL2R2 carbon phases have also been demonstrated. Given the diversity of CNTs from various chiralities, diameters, and arrangements, pressure-induced CNT polymerization provides a promising approach to produce numerous novel metastable carbons exhibiting unique electronic, optical, and mechanical characteristics.Розглянуто експериментальні та теоретичні дослідження з індукованою тиском полігонізації, овалізації, деформації у формі бігової доріжки і полімеризації вуглецевих нанотрубок (ВНТ). Обговорено відповідні електронні, оптичні і механічні зміни, що супроводжують ці процеси. Також продемонстровано перетворення в ВНТ у формі крісла (n, n), зібраних в пучок (n = 2, 3, 4, 6 і 8) під гідростатичним або негідростатичним тиском в нові вуглецеві алотропи, в тому числі недавно запропоновані надтверді bct-C₄, Cco-C₈ і B-B1AL2R2-вуглецеві фази. Різноманітність ВНТ з різними хіральністю, діаметрами та упаковками, а також полімеризація ВНТ, викликана тиском, забезпечує перспективний підхід для отримання численних нових метастабільних вуглецевих фаз, що демонструють унікальні електронні, оптичні і механічні характеристики.Рассмотрены экспериментальные и теоретические исследования по индуцированной давлением полигонизации, овализации, деформации в форме беговой дорожки и полимеризации углеродных нанотрубок (УНТ). Обсуждены соответствующие электронные, оптические и механические изменения, сопровождающие эти процессы. Также продемонстрированы преобразования в УНТ в форме кресла (n, n), собранных в пучок (n = 2, 3, 4, 6 и 8) под гидростатическим или негидростатическим давлением в новые углеродные аллотропы, в том числе недавно предложенные сверхтвердые bct-C₄, Cco-C₈ и B-B1AL2R2-углеродные фазы. Разнообразие УНТ с различными хиральностью, диаметрами и упаковками, а также полимеризация УНТ, вызванная давлением, обеспечивает перспективный подход для получения многочисленных новых метастабильных углеродных фаз, демонстрирующих уникальные электронные, оптические и механические характеристики

Ultrastrong conductive in situ composite composed of nanodiamond incoherently embedded in disordered multilayer graphene

Traditional ceramics or metals cannot simultaneously achieve ultrahigh strength and high electrical conductivity. The elemental carbon can form a variety of allotropes with entirely different physical properties, providing versatility for tuning mechanical and electrical properties in a wide range. Here, by precisely controlling the extent of transformation of amorphous carbon into diamond within a narrow temperature–pressure range, we synthesize an in situ composite consisting of ultrafine nanodiamond homogeneously dispersed in disordered multilayer graphene with incoherent interfaces, which demonstrates a Knoop hardness of up to ~53 GPa, a compressive strength of up to ~54 GPa and an electrical conductivity of 670–1,240 S m(–1) at room temperature. With atomically resolving interface structures and molecular dynamics simulations, we reveal that amorphous carbon transforms into diamond through a nucleation process via a local rearrangement of carbon atoms and diffusion-driven growth, different from the transformation of graphite into diamond. The complex bonding between the diamond-like and graphite-like components greatly improves the mechanical properties of the composite. This superhard, ultrastrong, conductive elemental carbon composite has comprehensive properties that are superior to those of the known conductive ceramics and C/C composites. The intermediate hybridization state at the interfaces also provides insights into the amorphous-to-crystalline phase transition of carbon

Cosmological distance indicators

We review three distance measurement techniques beyond the local universe: (1) gravitational lens time delays, (2) baryon acoustic oscillation (BAO), and (3) HI intensity mapping. We describe the principles and theory behind each method, the ingredients needed for measuring such distances, the current observational results, and future prospects. Time delays from strongly lensed quasars currently provide constraints on $H_0$ with < 4% uncertainty, and with 1% within reach from ongoing surveys and efforts. Recent exciting discoveries of strongly lensed supernovae hold great promise for time-delay cosmography. BAO features have been detected in redshift surveys up to z <~ 0.8 with galaxies and z ~ 2 with Ly-$\alpha$ forest, providing precise distance measurements and $H_0$ with < 2% uncertainty in flat $\Lambda$CDM. Future BAO surveys will probe the distance scale with percent-level precision. HI intensity mapping has great potential to map BAO distances at z ~ 0.8 and beyond with precisions of a few percent. The next years ahead will be exciting as various cosmological probes reach 1% uncertainty in determining $H_0$, to assess the current tension in $H_0$ measurements that could indicate new physics.Comment: Review article accepted for publication in Space Science Reviews (Springer), 45 pages, 10 figures. Chapter of a special collection resulting from the May 2016 ISSI-BJ workshop on Astronomical Distance Determination in the Space Ag

Clustering Algorithms: Their Application to Gene Expression Data

Gene expression data hide vital information required to understand the biological process that takes place in a particular organism in relation to its environment. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks and the volume of genes present increase the challenges of comprehending and interpretation of the resulting mass of data, which consists of millions of measurements; these data also inhibit vagueness, imprecision, and noise. Therefore, the use of clustering techniques is a first step toward addressing these challenges, which is essential in the data mining process to reveal natural structures and iden-tify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding gene functions, cellular processes, and subtypes of cells, mining useful information from noisy data, and understanding gene regulation. The other benefit of clustering gene expression data is the identification of homology, which is very important in vaccine design. This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure

Amyloid and tau pathology associations with personality traits, neuropsychiatric symptoms, and cognitive lifestyle in the preclinical phases of sporadic and autosomal dominant Alzheimer’s disease

Background Major prevention trials for Alzheimer’s disease (AD) are now focusing on multidomain lifestyle interventions. However, the exact combination of behavioral factors related to AD pathology remains unclear. In 2 cohorts of cognitively unimpaired individuals at risk of AD, we examined which combinations of personality traits, neuropsychiatric symptoms, and cognitive lifestyle (years of education or lifetime cognitive activity) related to the pathological hallmarks of AD, amyloid-β, and tau deposits. Methods A total of 115 older adults with a parental or multiple-sibling family history of sporadic AD (PREVENT-AD [PRe-symptomatic EValuation of Experimental or Novel Treatments for AD] cohort) underwent amyloid and tau positron emission tomography and answered several questionnaires related to behavioral attributes. Separately, we studied 117 mutation carriers from the DIAN (Dominant Inherited Alzheimer Network) study group cohort with amyloid positron emission tomography and behavioral data. Using partial least squares analysis, we identified latent variables relating amyloid or tau pathology with combinations of personality traits, neuropsychiatric symptoms, and cognitive lifestyle. Results In PREVENT-AD, lower neuroticism, neuropsychiatric burden, and higher education were associated with less amyloid deposition (p = .014). Lower neuroticism and neuropsychiatric features, along with higher measures of openness and extraversion, were related to less tau deposition (p = .006). In DIAN, lower neuropsychiatric burden and higher education were also associated with less amyloid (p = .005). The combination of these factors accounted for up to 14% of AD pathology. Conclusions In the preclinical phase of both sporadic and autosomal dominant AD, multiple behavioral features were associated with AD pathology. These results may suggest potential pathways by which multidomain interventions might help delay AD onset or progression

Search for leptophobic Z ' bosons decaying into four-lepton final states in proton-proton collisions at root s=8 TeV

Peer reviewe

Search for heavy resonances decaying into a vector boson and a Higgs boson in final states with charged leptons, neutrinos, and b quarks

Peer reviewe

Measurements of differential production cross sections for a Z boson in association with jets in pp collisions at root s=8 TeV

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