This study presents a comprehensive mathematical simulation using Simulink software for a novel hybrid waste-to-energy sustainable system tailored for restaurant communities. The system integrates a microbial fuel cel...
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This study presents a comprehensive mathematical simulation using Simulink software for a novel hybrid waste-to-energy sustainable system tailored for restaurant communities. The system integrates a microbial fuel cell with subsystems for biodiesel production, anaerobic biogas digestion, methane reforming, and methanol production. The hybrid system aims to convert 500 kg of waste cooking oil, 2000 kg of food waste, and wastewater produced daily by the community into valuable resources. Results revealed that the system can produce 319,376 kWh of electricity, 14.6 t of H2 gas, 116.8 t of CO2 and 525 m3 of purified water annually. These outputs provide a net saving/profit of $245,530 with a return on investment of just 6 months. Additionally, the system demonstrates environmental benefits by reducing annual emissions by 200 tCO2 and 27.450 tCH4. The findings highlight the hybrid system's effectiveness in mitigating environmental impact, generating clean energy and valuable fuels, and advancing sustainable waste management practices within restaurant communities.
The rapid expansion of the Internet of Things (IoT) has significantly increased the prevalence of malware targeting IoT devices. Although machine learning models offer promising solutions for automatic malware detecti...
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The rapid expansion of the Internet of Things (IoT) has significantly increased the prevalence of malware targeting IoT devices. Although machine learning models offer promising solutions for automatic malware detection, they are increasingly vulnerable to adversarial attacks. These attacks exploit the model's feedback loop to iteratively refine malware, producing adversarial samples that evade detection. As such, enhancing the robustness of these models is of paramount importance. Our research introduces a novel approach to bolster malware detection by retaining additional semantic information within the execution order analysis of malware programs. The method significantly improves the resilience of detection models against adversarial samples and implements two adversarial attack methods to rigorously test our model's robustness by generating authentic adversarial examples for validation. We highlight the critical impact of preserving semantic integrity in malware detection and present a solution to counteract the growing threat of adversarial attacks in IoT environments.
PurposeIn this article, we present the numerical solution of fractional Sturm-Liouville problems by using generalized shifted Chebyshev ***/methodology/approachWe combine right Caputo and left Riemann-Liouville fracti...
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PurposeIn this article, we present the numerical solution of fractional Sturm-Liouville problems by using generalized shifted Chebyshev ***/methodology/approachWe combine right Caputo and left Riemann-Liouville fractional differential operators for the construction of fractional Sturm-Liouville operators. The proposed algorithm is developed using operational integration matrices of generalized shifted Chebyshev polynomials. We introduce a new bound on the coefficients of the shifted. Chebyshev polynomials subsequently employed to establish an upper bound for error in the approximation of a function by shifted Chebyshev *** have solved fractional initial value problems, terminal value problems and Sturm-Liouville problems by plotting graphs and comparing the results. We have presented the comparison of approximated solutions with existing results and exact numerical solutions. The presented numerical problems with satisfactory results show the applicability of the proposed method to produce an approximate solution with ***/valueThe presented method has been applied to a specific class of fractional differential equations, which involve fractional derivatives of a function with respect to some other function. Keeping this in mind, we have modified the classical Chebyshev polynomials so that they involve the same function with respect to which fractional differentiation is performed. This modification is of great help to analyze the newly introduced polynomials from analytical and numerical point of view. We have compared our numerical results with some other numerical methods in the literature and obtained better results.
A compressible and highly elastic sponge thermoelectric generator (S-TEG) that exhibits excellent mechanical properties under an applied compressive force was fabricated. Carbon nanotubes were surface-modified via oxi...
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A compressible and highly elastic sponge thermoelectric generator (S-TEG) that exhibits excellent mechanical properties under an applied compressive force was fabricated. Carbon nanotubes were surface-modified via oxidation (m-CNTs) and combined with reduced graphene oxide (rGO) to form an m-CNT@rGO composite. A thermoelectric composite with a cylindrical sponge structure was fabricated by adding m-CNT@rGO to polydimethylsiloxane (PDMS) and sodium chloride, followed by chemical doping with FeCl3 (p-type) and poly(ether imide) (n-type) solutions to improve the thermoelectric effect. A stand-alone continuous thermoelectric module design was realized by connecting the cylinders in series;the electrodes were connected by attaching copper sheets to the top and bottom of the S-TEGs. The system generated a voltage of 24 mV at a temperature difference of 20 K. The sponge cylinder with a 20 mm diameter, 15 mm height, and 1.5 cm distance between two cylinders resulted in the best thermoelectric effect, producing a voltage of 300 mV and maintaining its original elasticity under 50% strain. The developed S-TEG with a three-dimensional sponge structure was applied to insoles to convert the wearer's body heat into electrical energy. The S-TEGs are expected to sustainably power various wearable electronic devices, realizing a truly self-powered system. This innovation is anticipated to not only improve the performance of wearable devices but also promote the development of smart insoles.
The management of agricultural wastes from agro-food processing industries is critical for sustainability, with growing attention towards utilizing green bioconversion processes. Pineapple leaf (PL) waste, a rich sour...
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The management of agricultural wastes from agro-food processing industries is critical for sustainability, with growing attention towards utilizing green bioconversion processes. Pineapple leaf (PL) waste, a rich source of hemicellulose, is a potential feedstock for industrial xylooligosaccharides (XOS) production for better health care. In the present work, a combined alcoholic deep eutectic solvent (DES) and ultrasound (50 % amplitude, 20 min) fractionation approach was applied to PL waste, resulting in improved xylan extraction (180 mg/g biomass) from the liquid fraction of the pretreated mixture. The DES (choline chloride/ethylene glycol, 1:2) was recycled for five cycles, maintaining 93 % extraction efficiency. Biorefining of XOS from xylan extracted by ethanol precipitation of pretreated PL liquid hydrolysate and dilute nitric acid (4%) for 1 h at 100 degrees C hydrolysis gave a maximum XOS yield (66.6 mg/g biomass) with xylobiose (24.3 mg/g biomass) as the most significant XOS. Mass balance analysis of the bioprocess revealed the effective conversion of waste biomass into bioproducts, ensuring minimal waste and maximum resource utilization. The integrated DES-ultrasound pretreatment substantiates the potential for sustainable XOS production from pineapple waste with significant biological activity.
PVDF membranes are widely used in water treatment applications, such as membrane distillation and ultrafiltration, due to their excellent chemical resistance and thermal stability. While various preparation methods ha...
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PVDF membranes are widely used in water treatment applications, such as membrane distillation and ultrafiltration, due to their excellent chemical resistance and thermal stability. While various preparation methods have been explored to enhance PVDF membranes, limited attention has been given to understanding how PVDF molecular weight influences membrane properties and performance. This study explores the influence of PVDF molecular weight on phase separation behavior, membrane morphology, and overall performance of membranes prepared via the plasma-assisted nonsolvent-induced phase separation (PANIPS) method. By systematically varying the molecular weight of PVDF (from 255 kDa to 1367 kDa) and the number of plasma treatment cycles, we achieved a spectrum of membrane morphologies and properties. It was observed that the membrane morphology evolved from a globular structure in a lower molecular weight PVDF to a stable bi-continuous structure in a higher molecular weight sample. Ternary phase diagrams and dynamic phase inversion studies were conducted to elucidate the mechanisms behind these structural transitions, revealing that a higher molecular weight PVDF results in broader demixing gaps but slower diffusion kinetics due to greater chain entanglement, thereby influencing phase separation dynamics. The anti-fouling capabilities of PANIPS membranes were validated through direct contact membrane distillation (DCMD) tests, where the membranes effectively treated hypersaline solutions containing 10 wt% NaCl and 1000 ppm Rose Bengal dye. This work demonstrates the versatility of the PANIPS method for tailoring membrane properties and emphasizes PVDF molecular weight as a critical factor in optimizing performance for diverse applications.
Accelerated ageing of cross-linked polyethylene (XLPE) insulated aerial bundled cables (ABC) installed at coastal regions for electric power distribution is a topic of major concern. Sudden failures caused by rapid in...
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Accelerated ageing of cross-linked polyethylene (XLPE) insulated aerial bundled cables (ABC) installed at coastal regions for electric power distribution is a topic of major concern. Sudden failures caused by rapid insulation deterioration initiate unexpected power shutdowns. Accurate prognosis of incipient failures in cables will enable maintenance agencies to plan repair or replacement activities well on time thus improving the reliability and availability of the transmission grid. In this research work, historical non-destructive evaluation (NDE) data was generated using infrared thermography of ABCs to ascertain cable degradation parameter. Historical NDE data embodies the progressive degradation experienced by the ABCs installed at harsh marine environment. The degradation growth in cable insulation, when subjected to rough environmental conditions, is non-linear coupled with non-Gaussian / multimodal noise distributions. Therefore, a renowned nonlinear Bayesian estimator namely Particle Filter (PF) is applied on the historical database to determine degradation growth evolution over time. The proposed framework is further complimented with f-step prediction scheme in future time to quantify the prediction accuracy of cable degradation growth in future where measurement data is not available. The so predicted results are then compared to the actual degradation in future. The prediction accuracy demonstrates the efficacy of proposed technique for prognosis of ABCs installed at different locations. Accurate state prediction in different life phases of ABCs further displays robustness of proposed technique in estimating actual degradation growth during the different life stages.
This article introduces an innovative connector terminal design for double data rate fifth-generation synchronous dynamic random-access memory (DDR5) connectors to enhance signal integrity in high-frequency memory sys...
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This article introduces an innovative connector terminal design for double data rate fifth-generation synchronous dynamic random-access memory (DDR5) connectors to enhance signal integrity in high-frequency memory systems. With the evolution of memory technology from DDR1 to DDR5, the requirements for higher transmission speeds and less signal distortion have necessitated more precise terminal designs. Simulations were conducted using ANSYS high-frequency structure simulator to assess the proposed stub design's high-frequency performance in terms of impedance, insertion loss (IL), return loss, and crosstalk (XT). Experimental results confirmed the superiority of the proposed design, which eliminates the 2.16 mm terminal stub from the conventional design. This modification minimized impedance variation, reduced IL by 0.2-0.4 dB in the 9-14.5 GHz frequency range, and enabled higher resonant frequencies in XT tests, thus enhancing signal integrity. These improvements hold significant promise for high-frequency applications, establishing a new design paradigm for DDR5 connector gold fingers and providing valuable insights for future high-speed memory interfaces.
The influence of small Y and Er additions (0.2 wt.%) on the supraplastic behavior and microstructural evolution of Ti-Al-Mo-V alloys during thermomechanical processing and superplastic deformation was investigated. Al...
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The influence of small Y and Er additions (0.2 wt.%) on the supraplastic behavior and microstructural evolution of Ti-Al-Mo-V alloys during thermomechanical processing and superplastic deformation was investigated. Alloying with 0.2% Y can effectively modify the cast structure, decreasing the mean grain size from 670 to 225 mu m, while addition of 0.2% Er exhibited no modifying effect. Thermomechanical processing promoted the refinement of oxide particles, resulting in compact particles measuring approximate to 0.2 mu m for the Er-bearing alloy and approximate to 0.1 mu m for the Y-bearing alloy. The alloys with Y and Er additions and the base alloy without additives exhibited close superplastic characteristics at temperatures of 775 and 875 degrees C, strain-rate sensitivity coefficient m = 0.45-0.55, and elongation approximate to 400-800% at strain rates of 1.10(-3) and 2.10(-4) s(-1). Alloying with Y and Er reduced the flow stress during superplastic deformation, which is attributed to the acceleration of recrystallization and globularization of the microstructure due to oxide particles. Also, the inhibiting effect of Y oxide particles on grain size during annealing in the single-phase beta-region and during superplastic deformation at low strain rates was revealed, while no effect was observed in the alloy with Er.
A comparative analysis of the effect of aging temperature in the interval of 175-250 degrees C as well as holding time on the stability of the achieved hardening and structural evolution of the aging products (theta &...
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A comparative analysis of the effect of aging temperature in the interval of 175-250 degrees C as well as holding time on the stability of the achieved hardening and structural evolution of the aging products (theta '-phase particles) is carried out for experimental wrought Al-6Cu-0.5Mn, Al-6Cu-0.5Mn-0.1Sn, and Al-6Cu-0.5Mn-0.1Sn-0.2Si alloys having tin and silicon micro additions in their compositions. Experimental studies into the structure are conducted using the methods of electronic scanning and transmission microscopy, while studies of physical and mechanical properties are conducted by analyzing changes in hardness (HV) and specific electrical conductivity during isothermal aging of alloys obtained in the form of flat products. A micro addition of tin significantly increases the peak hardness of alloys in the entire studied interval of aging temperatures. The increase in temperature of up to 250 degrees C, compared to aging at a lower temperature of 175 degrees C, leads to a natural decrease in the peak hardness of the studied alloys, although to varying degrees. The peak hardness of tin-containing alloys decreased only by 10% (up to 140 HV) compared to 18% (up to 110 HV) in the base Al-6Cu-0.5Mn alloy. A gradual decrease in hardness of all alloys at different rates after achieving peak hardening during prolonged holding and aging at 250 degrees C is shown. At the same time, the rate of decrease in hardness of the Al-6Cu-0.5Mn-0.1Sn-0.2Si alloy with a silicon micro addition during ongoing annealing is significantly lower than that of other two alloys. An analysis of the microstructure showed that the proportion of more dispersed particles is significantly higher in the Al-6Cu-0.5Mn-0.1Sn-0.2Si alloy with a silicon micro addition compared to that in the Al-6Cu-0.5Mn-0.1Sn alloy. This circumstance may explain the observed higher hardness of the alloy with a small silicon addition after long-term high-temperature annealing.
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