Hasil untuk "Oils, fats, and waxes"

J. R.

Du Anqi, Wen Ming, Dong Zonghao et al.

Downhole throttling technology is an efficient means of hydrate prevention and control. How to establish an effective throttling pressure difference in a reasonable time to ensure that the wellhead pressure and temperature are quickly reduced to a safe range has become the key to the successful implementation of downhole throttling technology. To address this issue， the OLGA transient multiphase flow simulator was used to conduct dynamic simulation on the pressure， temperature and production during flowing of gas wells. Then， the flow and heat transfer characteristics in the wellbore under different choke diameters and flowing production conditions were analyzed， and the risk of hydrate formation was predicted. The research results show that the choke diameter significantly affects the time required for the wellhead pressure to decline to the delivery pressure and the stable production rate. Smaller choke diameter （e.g. 4.3 mm） increases the downhole flow resistance， accelerates the decline of wellhead pressure， but limits the stable production rate. Larger choke diameters （e.g. 5.4 mm and 6.0 mm） prolong the pressure decline time， but can achieve higher stable production rates in long-term production. Under the conditions of downhole throttle valve with small choke diameter and high flowing production rate， the post-valve temperature recovers fast， and the risk of freezing blockage is low. However， under the conditions of downhole throttle valve with large choke diameter and low flowing production rate， the post-valve temperature remains below the hydrate formation temperature for a long time， and the risk of freezing blockage increases significantly. In actual production， it is recommended to comprehensively consider surface processing capacity， gas reservoir development requirements and safe production demands to formulate the optimal downhole throttling scheme. The research results provide a scientific basis for the design and optimization of downhole throttling technology in high-pressure gas wells.

Javier Martínez-Aguinaga

It is well known that every complex contact $3$-manifold, when regarded as a real manifold, gives rise to a fat $(4,6)$-distribution that admits two Reeb directions. Nonetheless, it was an open question whether the converse was true. This was not known even at the level of germs. The present work completely answers this question in the negative. We construct the first example of a fat distribution with two Reeb directions that does not support a complex contact structure anywhere, not even locally nor up to diffeomorphism. This result answers an open question by A. Bhowmick. In the second part of this work we prove a stronger result. By applying suitable $C^\infty$-perturbations to our construction, we show that the space of complex-contact germs has infinite codimension within the space of fat $(4,6)$-distribution germs with Reeb directions.

Bojacá Carlos Ricardo, Hernández-Rendón Diego Alejandro, Tupaz-Vera Andrés Alejandro et al.

Oil palm harvesting operations, particularly the collection and transportation of fresh fruit bunches (FFB), represent a significant portion of production costs and rely heavily on manual labor. The spatial configuration of fruit collection points (FCPs) directly impacts operational efficiency, yet their placement is often determined through empirical criteria rather than systematic optimization. This study presents a methodology for optimizing FCP locations in oil palm plantations, taking into account spatial yield variability and labor productivity constraints. Using data from a 148.1-ha plantation in Colombia’s eastern region, we first characterized the relationship between plot productivity and harvesting efficiency, finding that the area serviced by harvest teams decreased from 4.0 to 1.7 ha day−1 as yield increased from 10 to 30 t ha−1. This relationship informed the subdivision of production plots into operational units, which served as input for a p-median optimization model to determine optimal FCP locations. The optimized configuration reduced the mean transport distance by 15.8% (from 239.7 m to 201.9 m) and the median distance by 10.6% (from 218.8 m to 195.7 m), while maintaining the current number of collection points. The methodology provides a data-driven approach to plantation infrastructure planning that could be particularly valuable for operations seeking to improve logistics efficiency without additional capital investment.

Zehua Chen, Wenjian Yue, Chengwen Wang

The incorporation of fibers represents a crucial technique for improving the mechanical properties and other relevant characteristics of cement-based composites (CBC), including concrete, cement mortar, and oil-well cement. Especially, carbon fiber (CF) has a great potential for reinforcing oil-well cement due to its high strength, modulus, stiffness, high temperature, corrosion and fatigue resistance as well as chemical stability. There is a huge amount of waste CFs all over the world which show better performance in cement industry, while their reuse will realize waste recovery (good environment impact) and greatly reduce cost. This review paper presents the recent progress of using CF in enhancing mechanical properties of CBC. We put high emphasis on the CF surface modification for reinforcing bond strength at the cement/CF interface. Comprehensive discussion with respect to effects of CF and modified CF on CBC properties is performed. The key properties of CBC examined in this study encompass mechanical characteristics (compressive strength, flexural strength, and tensile strength), dimensional stability (shrinkage behavior), durability indicators (water absorption and permeability), and fracture-related properties (toughness, crack resistance, and impact performance). Thus, suggestions are given for the future study and application of CF in oil-well cement.

Eduardo Fernández, Álvaro del Pino, Wei Zhou

We investigate the $h$-principle problem for fat distributions. These are maximally non-integrable distributions with natural symplectisations and contactisations, that generalize contact distributions to higher corank. We focus on the corank-$2$ case, where we study a natural class of submanifolds, which we call prelegendrians. Their key feature is that they admit a canonical Legendrian lift to the contactisation. Our main results state that the $h$-principle fails for these submanifolds in all dimensions. This is the first example of rigidity in the study of maximally non-integrable distributions, outside of contact topology. First, we find an infinite family of $(2n+1)$-tori in the standard fat $(\mathbb{C}^{2n+1},\mathcal{D}_{\mathrm{std}})$, with the following two properties: (1) They all represent the same formal prelegendrian class, (2) but they are not prelegendrian isotopic because they are distinguished by pseudoholomorphic curve invariants of their Legendrian lift. Secondly, we define the notion of prelegendrian stabilization in $(\mathbb{C}^{2n+1},\mathcal{D}_{\mathrm{std}})$. This allows us to take an arbitrary prelegendrian and produce another one, in the same formal class, whose Legendrian lift is loose. In order to prove these results we also develop the fundamentals of the theory of prelegendrians. This includes: (1) introducing the notion of front projection in $(\mathbb{C}^{2n+1},\mathcal{D}_{\mathrm{std}})$, (2) proving that pseudoholomorphic curve invariants are robust under perturbations of the fat structure, allowing us to transport our results to non-standard fat structures, (3) introducing a zooming argument showing that any fat structure in dimension $6$ admits prelegendrians.

WU Turong, CHEN Jinding, ZHANG Qun et al.

Nuclear magnetic resonance (NMR) imaging is an advanced technology for core-scale heterogeneity analysis. Affected by rock complexity and encoding technology, existing methods are not really effective. 2D/3D nuclear magnetic resonance technology based on gradient fields is easy to image but has a low signal-to-noise ratio. The traditional T2 method (frequency coding/phase coding) without gradient field is in low efficiency. This study proposes a tomography method based on constant gradient coded 1D T2 spectrum, which can achieve small imaging data volume, high signal-to-noise ratio and more complete signal. Tomographic T2 spectrum images and their heat distribution can effectively characterize the effects of capillary force and diagenesis on the non-uniform distribution of fluids. In the oil-saturated state, the difference between T2 spectrum layers reflects the influence of diagenesis. The heat change of the image in the high saturation stage mainly reflects the displace pattern of low capillary force controlled free oil. After complete displacement, the capillary force enters a stable state, and the axial heat reflects the difference of micro-pore content that filled with adsorbed oil. The new technology has achieved good results in gas displacement experiments of cemented sandstone, and is expected to play an important role in the analysis of seepage laws of strong heterogeneous rocks.

L Rochit, Nithish Kumar N, Devi Priya V S et al.

The ocean ecology is badly impacted by large-scale oil spills, plastic waste, and chemical pollution, which destroy ecosystems and endanger marine life. Acknowledging the detrimental effects of oil spills on ecosystems, our research aims to establish the foundation for creative methods to lessen their impact. With an emphasis on the containment and prediction of oil spills, this research investigates the potential of acoustic levitation as a cutting-edge technique for environmental cleanup. Effectively separating and eliminating pollutants without causing additional ecological harm is a major issue for traditional oil spill cleanup techniques. Acoustic levitation provides a non-invasive, accurate, and effective alternative by using sound waves to precisely and subtly separate oil droplets from water in controlled environments. This proposed approach can reduce the negative effects on the environment and increase the efficacy of cleanup efforts. The findings have been examined and assessed by proof of concept experiments with oil droplets, identifying the relationship between the intensity of ultrasonic pressure and the proportion of oil droplets collected.

Bal Krishan, Preetika Rastogi, D. Chaitanya Kumar Rao et al.

Emulsion fuels have the potential to reduce both particulate matter and NOx emissions and can potentially improve the efficiency of combustion engines. However, their limited stability remains a critical barrier to practical use as an alternative fuel. In this study, we explore the evaporation behavior of thermodynamically stable water-in-oil microemulsions. The water-in-oil microemulsion droplets prepared from different types of oil were acoustically levitated and heated using a continuous laser at different irradiation intensities. We show that the evaporation characteristics of these microemulsions can be controlled by varying water-to-surfactant molar ratio (ω) and volume fraction of the dispersed phase (φ). The emulsion droplets undergo three distinct stages of evaporation, namely pre-heating, steady evaporation, and unsteady evaporation. During the steady evaporation phase, increasing φ reduces the evaporation rate for a fixed ω. It is observed that the evaporation of microemulsion is governed by the complex interplay between its constituents and their properties. We propose a parameter (η) denoting the volume fraction ratio between volatile and non-volatile components, which indicates the cumulative influence of various factors affecting the evaporation process. The evaporation of microemulsions eventually leads to the formation of solid spherical shells, which may undergo buckling. The distinction in the morphology of these shells is explored in detail using SEM imaging.

Antetti Tampubolon

Lip balm is a cosmetic preparation with main components such as waxes, fats and oils. The purpose of this study was to determine whether Aloe vera and red dragon fruit extracts could be formulated as moisturizers and natural dyes in lip balm preparations. The study was carried out experimentally, including the formulation of preparations with concentrations of Aloe Vera extract 3%, 6%, 10%, and Red Dragon Fruit extract 3%, 5%, 7%. Examination of the physical quality of the preparation, namely homogeneity test, stability during 28 days of storage at room temperature, melting point, pH, and preference test. The results showed that (F1) with a concentration of 3% aloe vera and 3% red dragon fruit met the requirements for homogeneity, melting point, pH, and stability tests, on (F2) with a concentration of 6% aloe vera and 5% red dragon fruit does not meet the requirements of the pH test, but meets the requirements of the homogeneity test, melting point test, and stability test. Whereas for (F3) with a concentration of 10% aloe vera and 7% red dragon fruit did not meet the homogeneity and pH test requirements, but met the melting point and stability test requirements. It can be concluded that Aloe Vera Extract and Red Dragon Fruit can be formulated into lip balm dosage forms. Differences in concentration variations can affect the moisture on the skin and the color of the preparation.

C. Schempp, K. Schwabe, Bernadett Kurz et al.

Gayatri Simanullang

Utilization of rice bran into oil through the extraction process. The content of rice bran can be used as a moisturizer in cosmetic preparation, especially lip balm. Lip balm is a cosmetic preparation with main components such as waxes, fats, and oils from natural or synthesized extracts to prevent lip dryness by increasing humidity and protecting it from adverse environmental effects. This research aims to determine the physical stability of lip balm preparations containing bran oil and the effect of bran oil concentration on the hedonic test results of lip balm preparations containing bran oil. This experimental research method focuses on the manufacture of lip balm preparations, the evaluation of lip balm preparations including organoleptic examination, homogeneity, melting point test, pH test, and spread-ability test during 28 days of storage. The results showed that all formulas of rice bran oil lip balm preparations met the requirements and the hedonic testing of rice bran oil lip balm preparations revealed that F1 (5% rice bran oil) was the panelist’s most preferred formula in terms of aroma, F2 (7.5% rice bran oil) was the most preferred formula in terms of texture, while F3 (10% rice bran oil) was the most preferred formula by panelists in terms of color.

董梦飞1，郭兴凤1，朱婷伟1，赵树超2 DONG Mengfei1, GUO Xingfeng1, ZHU Tingwei1, ZHAO Shuchao2

旨在为大豆蛋白在冷冻发酵面团中的应用提供一定的理论依据，对添加大豆分离蛋白（SPI）、质构化大豆分离蛋白（TSP）、水解大豆分离蛋白(SPH)的冷冻发酵面团馒头及冷冻发酵面团进行研究，分析了添加不同种类大豆蛋白的冷冻发酵面团馒头的理化指标（比容、水分含量、pH），并通过测定冷冻发酵面团的二硫键含量、蛋白质二级结构和微观结构，探讨不同种类大豆蛋白对冷冻发酵馒头品质的影响机制。结果表明：添加SPH的发酵面团冷冻储藏前后所蒸制的馒头比容变化最小，在冷冻储藏40 d时蒸制的馒头比容相比冷冻储藏10 d增加了4.59%；同一冷冻储藏时间下添加SPH的发酵面团蒸制的馒头水分含量最低；添加大豆蛋白可以减小在冷冻储藏过程中发酵面团馒头pH的下降速率，至少可延长冷冻发酵面团10 d的保质期；通过傅里叶红外光谱和激光共聚焦对冷冻发酵面团蛋白质结构分析，得出添加3种大豆蛋白均会降低面筋蛋白网络结构的均匀性和连续性，SPI和TSP对面筋蛋白网络结构的影响小于SPH，但在冷冻储藏过程中添加SPH的发酵面团的面筋蛋白网络结构相对较为稳定。综上，大豆蛋白与面筋蛋白通过二硫键和非共价键相互作用，改变面筋蛋白网络结构的均匀性和连续性，从而引起馒头品质变化。In order to provide some theoretical basis for the application of soy protein in frozen fermented dough, the frozen fermented dough buns and frozen fermented doughs with soy protein isolates(SPI), texturised soy protein isolates(TSP), hydrolysed soy protein isolates (SPH)added were studied, the physicochemical indexes (specific volume, water content, pH) of frozen fermented dough buns added with different kinds of soy proteins were analysed, and the effect mechanism of different kinds of soy proteins on the quality of frozen fermented dough buns was investigated by determining the disulphide bond content, the secondary structure and microstructure of proteins in the frozen fermented doughs. The results showed that the specific volume of steamed buns before and after frozen storage of fermented dough with SPH had the smallest change, and the specific volume of steamed buns after 40 d of frozen storage increased by 4.59% compared with 10 d of frozen storage. The water content of steamed buns with SPH was the lowest under the same frozen storage time. The addition of soy protein could reduce the rate of pH drop of fermented dough buns during frozen storage, and could extend the shelf life of frozen fermented doughs by at least 10 d.The protein structure analysis of frozen fermented dough by Fourier infrared and laser confocal results showed that the addition of three soy proteins reduced the uniformity and continuity of gluten protein network structure.The effects of SPI and TSP on the gluten protein network structure were less than those of SPH, but the gluten protein network structure of fermented dough with SPH added during frozen storage was relatively stable.In summary, soy protein and gluten protein interact through S—S and non-covalent bonds to change the uniformity and continuity of the gluten protein network structure, causing changes in the quality of steamed buns.

A. Spielman, Judit Forrai

Wax is the oldest dental material still in use today. Chemically, wax is an ester containing a long-chain alcohol and a long-chain fatty acid. Today, dental waxes are a mixture of animal, vegetable, and mineral origin, as well as dyes, oils, fats, gums, and resins; the later components change the wax’s physical properties such as melting range, fluidity, ductility, thermal expansion or contraction, and distortion with time. Each component is added to attain the physical properties desirable for a particular application. Natural waxes like carnauba wax are produced from plants; bees make beeswax, while paraffin is derived from minerals.

Rajneesh Kashyap, Mohit Kalra, Arti Kashyap

Oil reservoirs around the globe are at their declining phase and in spite of enormous effectiveness of Enhanced Oil Recovery(EOR) in the Tertiary Stage. This process still bypasses some oil reason being surface forces responsible for holding oil inside the rock surface which are not being altered by the application of existing technologies. The processes coming under Tertiary Section Supplements primary and secondary sections. However, the mechanism of operating is different in both. Nanoparticles are showing a significant role in EOR techniques and is a promising approach to increase crude oil extraction. This is due to the fact that size of nanoparticles used for EOR lies in the range of 1-100 nm. It is also an interesting fact that in different operational conditions and parameters, the performance of nanoparticles also vary and some are more effective than others, which leads to various levels of recovery in the EOR process. In the present study, we intend to summarize a report having an up to date status on nanotechnology assisted EOR mechanisms where nanoparticles are used as nano-catalysts, nano-emulsions and nanoparticles assisted EOR mechanisms to destabilize the oil layer on carbonate surface. This review also highlights the various mechanisms such Gibb's free energy, wettability alteration, and Interfacial Tension Reduction (ITR) including interaction of available nanoparticles with reservoirs. Experimental measurements for a wide range of nanoparticles are not only expensive but are challenging because of the relatively small size, especially for the measurements of thinner capillaries of a nanoscale diameter. Therefore, we considered computational simulations as a more adequate approach to gain more microscopic insights into the oil displacement process to classify the suitability of nanomaterials.

Shane Laibach, Egor Vinogradov, Jasper Stedman et al.

Nanofluids have the potential to enhance oil recovery through the structural disjoining pressure, a pressure developed when nanoparticles concentrate at the three-phase contact line. A model microfluidic porous network is used to measure the percentage of oil displaced from this channel as the volume fraction of a Triton X-100 micelle nanofluid is varied from 0 - 30%. The percentage of oil displaced varies nearly linearly with micellar nanoparticle volume fraction starting with 39% using deionized water and 89% using a volume fraction of 30%. While the trend is clear, significant variability between experiments was observed for a fixed nanofluid volume fraction. This indicates that surface energy heterogeneity is important for the nanofluid oil displacement performance.

Pranay Pasula

The scarcity of task-labeled time-series benchmarks in the financial domain hinders progress in continual learning. Addressing this deficit would foster innovation in this area. Therefore, we present COB, Crude Oil Benchmark datasets. COB includes 30 years of asset prices that exhibit significant distribution shifts and optimally generates corresponding task (i.e., regime) labels based on these distribution shifts for the three most important crude oils in the world. Our contributions include creating real-world benchmark datasets by transforming asset price data into volatility proxies, fitting models using expectation-maximization (EM), generating contextual task labels that align with real-world events, and providing these labels as well as the general algorithm to the public. We show that the inclusion of these task labels universally improves performance on four continual learning algorithms, some state-of-the-art, over multiple forecasting horizons. We hope these benchmarks accelerate research in handling distribution shifts in real-world data, especially due to the global importance of the assets considered. We've made the (1) raw price data, (2) task labels generated by our approach, (3) and code for our algorithm available at https://oilpricebenchmarks.github.io.

HVR Mittal, Mohamad Abed El Rahman Hammoud, Ana K. Carrasco et al.

A risk analysis is conducted considering several release sources located around the NEOM shoreline. The sources are selected close to the coast and in neighboring regions of high marine traffic. The evolution of oil spills released by these sources is simulated using the MOHID model, driven by validated, high-resolution met-ocean fields of the Red Sea. For each source, simulations are conducted over a 4-week period, starting from first, tenth and twentieth days of each month, covering five consecutive years. A total of 48 simulations are thus conducted for each source location, adequately reflecting the variability of met-ocean conditions in the region. The risk associated with each source is described in terms of amount of oil beached, and by the elapsed time required for the spilled oil to reach the NEOM coast, extending from the Gulf of Aqaba in the North to Duba in the South. A finer analysis is performed by segmenting the NEOM shoreline, based on important coastal development and installation sites. For each subregion, source and release event considered, a histogram of the amount of volume beached is generated, also classifying individual events in terms of the corresponding arrival times. In addition, for each subregion considered, an inverse analysis is conducted to identify regions of dependence of the cumulative risk, estimated using the collection of all sources and events considered. The transport of oil around the NEOM shorelines is promoted by chaotic circulations and northwest winds in summer, and a dominant cyclonic eddy in winter. Hence, spills originating from release sources located close to the NEOM shorelines are characterized by large monthly variations in arrival times, ranging from less than a week to more than two weeks. Large variations in the volume fraction of beached oil, ranging from less then 50\% to more than 80% are reported.

Guoqiang LIU, Renbin GONG, Yujiang SHI et al.

Based on the well logging knowledge graph of hydrocarbon-bearing formation (HBF), a Knowledge-Powered Neural Network Formation Evaluation model (KPNFE) has been proposed. It has the following functions: (1) extracting characteristic parameters describing HBF in multiple dimensions and multiple scales; (2) showing the characteristic parameter-related entities, relationships, and attributes as vectors via graph embedding technique; (3) intelligently identifying HBF; (4) seamlessly integrating expertise into the intelligent computing to establish the assessment system and ranking algorithm for potential pay recommendation. Taking 547 wells encountered the low porosity and low permeability Chang 6 Member of Triassic in the Jiyuan Block of Ordos Basin, NW China as objects, 80% of the wells were randomly selected as the training dataset and the remainder as the validation dataset. The KPNFE prediction results on the validation dataset had a coincidence rate of 94.43% with the expert interpretation results and a coincidence rate of 84.38% for all the oil testing layers, which is 13 percentage points higher in accuracy and over 100 times faster than the primary conventional interpretation. In addition, a number of potential pays likely to produce industrial oil were recommended. The KPNFE model effectively inherits, carries forward and improves the expert knowledge, nicely solving the robustness problem in HBF identification. The KPNFE, with good interpretability and high accuracy of computation results, is a powerful technical means for efficient and high-quality well logging re-evaluation of old wells in mature oilfields.

Fang Chen, Heiko Balzter, Feixiang Zhou et al.

Successful implementation of oil spill segmentation in Synthetic Aperture Radar (SAR) images is vital for marine environmental protection. In this paper, we develop an effective segmentation framework named DGNet, which performs oil spill segmentation by incorporating the intrinsic distribution of backscatter values in SAR images. Specifically, our proposed segmentation network is constructed with two deep neural modules running in an interactive manner, where one is the inference module to achieve latent feature variable inference from SAR images, and the other is the generative module to produce oil spill segmentation maps by drawing the latent feature variables as inputs. Thus, to yield accurate segmentation, we take into account the intrinsic distribution of backscatter values in SAR images and embed it in our segmentation model. The intrinsic distribution originates from SAR imagery, describing the physical characteristics of oil spills. In the training process, the formulated intrinsic distribution guides efficient learning of optimal latent feature variable inference for oil spill segmentation. The efficient learning enables the training of our proposed DGNet with a small amount of image data. This is economically beneficial to oil spill segmentation where the availability of oil spill SAR image data is limited in practice. Additionally, benefiting from optimal latent feature variable inference, our proposed DGNet performs accurate oil spill segmentation. We evaluate the segmentation performance of our proposed DGNet with different metrics, and experimental evaluations demonstrate its effective segmentations.