Nielsen Model Research Articles

Nanosized boron nitride-incorporated polyvinyl alcohol composites with TEMPO-oxidized cellulose nanofibers as ultrathin thermal interface materials

With the miniaturization and dense packing of electrical devices and mobility platforms, the effective thermal management at the interfaces of components in compact form factors is essential to overcome the performance limits and ensure the stability. Herein, we report the development of assembly of nanosized boron nitrides (BN) and TEMPO-oxidized cellulose nanofibers (T-CNFs) in polyvinyl alcohol (PVA) composites as ultrathin thermal interface materials (TIMs). BN nanoparticles (average thickness of 3.8–4.0 nm, lateral size of 90–100 nm, and aspect ratio of 25) were produced with a yield exceeding 80 % from the chemical treatment of hexagonal BN with NaOH and subsequent ball milling. TEMPO-oxidized cellulose nanofibers (T-CNFs) were added to mechanically reinforce the PVA-based matrix, while by the functionalization with OH– groups, the BN particles dispersed readily in the PVA solution, obtaining ultrathin nanosized BN/PVA/T-CNF composite films (∼50 µm). In contrast to the expected low thermal conductivity due to surface defects and high contact resistances typical of nanosized BN, composite films containing 50 wt% nanosized BN exhibited significantly high in-plane and through-plane thermal conductivities of 11.13 and 1.22 W/mK, respectively. Comparative analysis based on the Lewis–Nielsen model revealed that the size, shape, and agglomeration state of the BN particles could highly influence the thermal conductivity of composite films. Furthermore, heat dissipation experiments reflecting practical conditions demonstrated the outstanding performance and thermal stability of nanosized BN/PVA/T-CNF films as TIMs. This study will inspire rational strategies to facilely incorporate nanosized BN to diverse composites, offering advanced thermal characteristics with mechanical robustness.

Option pricing in a stochastic delay volatility model

This work introduces a new stochastic volatility model with delay parameters in the volatility process, extending the Barndorff–Nielsen and Shephard model. It establishes an analytical expression for the log price characteristic function, which can be applied to price European options. Empirical analysis on S&P500 European call options shows that adding delay parameters reduces mean squared error. This is the first instance of providing an analytical formula for the log price characteristic function in a stochastic volatility model with multiple delay parameters. We also provide a Monte Carlo scheme that can be used to simulate the model.

Option pricing for Barndorff–Nielsen and Shephard model by supervised deep learning

This paper aims to develop a supervised deep learning scheme to compute call option prices for the Barndorff-Nielsen and Shephard model with a non-martingale asset price process having infinite active jumps. In our deep learning scheme, teaching data are generated through the Monte Carlo method developed by Arai and Imai [(2024). Monte Carlo simulation for Barndorff-Nielsen and Shephard model under change of measure, Mathematics and Computers in Simulation, 218, 223–234]. Moreover, the BNS model includes many parameters, which makes the deep learning accuracy worse. Therefore, we will create another input parameter using the Black–Scholes formula. As a result, the accuracy is improved dramatically.

E-Catalog Promotion of Fishermen Business Group with User Centered Design Method

This research aims to design a promotional e-catalog for fishing business groups using the User Centered Design (UCD) method to improve the quality of their promotional services online. The partners in this research are the Fisheries Supervisory Community Group in Batu Basar Village, Nongsa District, Batam City, Riau Islands. So far, this group and fishermen have often faced obstacles in promoting their products effectively to potential consumers, especially in the rapidly developing digital era. The UCD method used in this research is a user-focused approach. The initial stage of research includes gathering information regarding the needs and preferences of potential users, including fishing business groups and potential consumers. This information was obtained through interviews, observations and literature studies. Based on the data collected, a promotional e-catalog was designed that took into account user needs and promotional objectives which included features such as complete product descriptions, product photos, price information, user testimonials and contact information. After the design is complete, the manufacturing stage is carried out and then continues to the testing stage involving potential users. This testing aims to maximize usability, efficiency and user satisfaction. The test results used the Nielsen model with five indicators with the results of Easy To Learn getting a score of 3.85, Efficiency To Use getting a score of 3.75, the Easy To Remember indicator getting a score of 3.85, and the Few Errors indicator getting a score of 4.05. Then the fun to use indicator has a value of 3.95.

Usability Study of the Mommy-Be App: Exploring the Experience of Breastfeeding Mothers in Eastern Indonesia

Objective: The rise of mobile health (mHealth) apps has brought attention to their potential in supporting breastfeeding mothers and preventing postpartum depression (PPD). This study aims to evaluate the usability of Mommy-Be, a mobile phone app designed to support breastfeeding women and help them to acknowledge of their mental health and breastfeeding efficacy during lactation period. Theoretical Framework: This study uses Usability theory to analyze the use of mHealth applications that proposed by Nielsen model. Method: This study combines quantitative and qualitative methods, that asses Mommy-Be app's usability among breastfeeding mothers using the Mobile Application Usability Questionnaire (MAUQ) and conducted in-depth interviews with a subset of participants. The study included 50 breastfeeding mothers in Makassar, Indonesia, who were primarily between the ages of 19 and 42 and had diverse educational and employment backgrounds. Four weeks after using the Mommy-Be app, revealed a generally positive impression of the application. Result: Based on MAUQ three dimensions, ease of use, interface satisfaction, usefulness, this study has been determined that the utilization of a Mommy-Be application is both acceptable and feasible as a mobile health (mHealth) solution for breastfeeding mothers. The mothers experience revealed diverse user impressions of the Mommy-Be application. Participants generally found it easy to use, with a favorable interface preference. Participants expressed various benefits of using Mommy-Be, including increased awareness of breastfeeding activities, assistance in meeting nutritional needs, and early detection of postpartum depressive disorders. Recommendations: To enhance the application's utility, participants suggested improvements, such as data export capabilities, better module integration, consideration of the target audience's resources regarding internet access and the inclusion of educational content, such as the provision of interconnection with multiple lactation counsellors.

Hot press machine user interface design based on usability evaluation

The success of a tool depends on user satisfaction, and users will feel satisfied if they can do their work effectively and efficiently. The Hotpress machine has been developed for the 3rd generation and is currently a tool for processing plastic waste into a substitute for plywood. This research aims to evaluate the usability level of the Hotpress G3 machine and design a user interface based on the evaluation results to make it easier for users to operate the machine. The Nielsen Attributes of Usability (NAU) Questionnaire is used to evaluate a machine's usability level, and Retrospective Think Aloud (RTA) is used to identify problems in user interaction with a product or system. The results obtained from this research are that based on the five attributes used, the Hotpress G3 machine has a low rating in four usability aspects based on the Nielsen model. Based on the results of the usability evaluation, a recommended user interface was designed, namely adding information to each control button according to its function, adding a sensor to determine whether the heating switch is on or not and providing information about the maximum temperature by adding an alarm to the engine box.

Usability evaluation of online transportation using Nielsen model

Maxim is one of the online transportation services in Indonesia. Based on the feedback provided by users on the App Store and Google Play store, there are still shortcomings, such as the application often having errors when used, GPS accuracy is not precise, and the system feeling difficult when canceling orders. Based on these problems, usability testing is needed. The method used in this research is usability testing based on the standard Nielsen Model conducted by five respondents. In this study, the Usability System Scale questionnaire was also filled in to get the satisfaction value carried out by 100 respondents using Maxim. The usability test results show that the respondents complained that the payment methods were not varied and there was no customer service chat. This usability test gives results on each indicator: the learnability value of 92%, the efficiency value of 0.42 goals/sec, the error value of 0.1, and the satisfaction value of 57.2.

Monte Carlo simulation for Barndorff–Nielsen and Shephard model under change of measure

The Barndorff–Nielsen and Shephard (BNS) model is a representative jump-type stochastic volatility model. Still, no method exists to compute option prices numerically for the non-martingale case with infinite active jumps. In this paper, selecting the minimal martingale measure (MMM) as a representative martingale measure, we develop two simulation methods for the BNS model under the MMM. The first method simulates the asset price at maturity and the Radon–Nikodym density of the MMM separately. On the other hand, the second method directly computes the asset price distribution under the MMM. In addition, we implement some numerical experiments to evaluate the performance of our simulation methods.

Re-Analysis of Historical Data and Model Calibration of Duration of Load Effect on Structural Timber

The duration of load (DOL) effect in structure timber refers to the degradation of strength and stiffness that occurs under long-term continuous loading. This paper investigated the DOL effect in structure timber using DOL tests and DOL damage models. Based on the empirical-fitted formulae, the DOL coefficients were derived for three long-term sustained loads in bending, tension perpendicular to grain, and shear parallel to grain, and the results were compared and analyzed with the Madison equation, Gerhards model, Nielsen model, and Foschi and Yao model derivations to verify the applicability of the DOL empirical model and the three DOL damage models. The results show that based on the historical data of the DOL tests, the Madison empirical formula was found to be better applied to the derivation of DOL coefficients under the bending and tension perpendicular to grain long-term sustained loading, and the derivation of DOL coefficients under shear loading is not satisfactory. Among the three DOL damage models, the Foschi and Yao model was better than the Gerhards and Nielsen models for fitting the DOL test results under bending, tension perpendicular to grain, and shear parallel to grain. The DOL coefficients derived based on the Foschi and Yao model are more comparable to test results and resemble those derived from the Madison formula.

Deep learning-based option pricing for Barndorff–Nielsen and Shephard model

This paper aims to develop a deep learning-based numerical method for option prices for the Barndorff–Nielsen and Shephard model, a representative jump-type stochastic volatility model. Using that option prices for the Barndorff–Nielsen and Shephard model satisfy a partial-integro differential equation, we will develop an effective numerical calculation method even in settings where conventional numerical methods are unavailable. In addition, we will implement some numerical experiments.

Effect of coir fiber reinforcement in PLA on the heat transfer characteristics – numerical simulations

The use of natural materials for thermal insulation over synthetic materials is on the rise due to their environmental friendliness, ease of availability, and cost-effectiveness. Additionally, the utilization of agro-waste-based materials in value-added applications promotes circular economy. The current study examines coir fiber and its insulating capability. Short coir fiber-reinforced Polylactic acid (PLA) is evaluated, with the fiber volume fraction ranging from 0 to 38%, to assess its suitability for thermal insulation applications through numerical simulations. Using commercial finite element-based software, the effective thermal conductivity of the natural fiber composite is calculated, which is the key property for insulation applications. A steady-state heat conduction analysis is performed on the composites with a periodic and uniformly oriented arrangement of coir fibers. Numerical results are validated using existing theoretical and empirical methods, such as the Parallel model, Halpin-Tsai, Lewis and Nielsen model. Initial investigations are done using simple geometries, revealing the effectiveness of incorporating coir into an environmentally friendly polymer matrix, PLA. The numerical results show that the effective thermal conductivity decreases with an increasing fiber volume fraction. This research concludes that adding coir fiber to the PLA matrix improves its insulation capabilities.

Enhanced tensile and barrier properties of modified LLDPE with rubbery materials and graphene nanoplatelets for packaging application

AbstractLinear low‐density polyethylene (LLDPE) is widely used in industries. It possesses remarkable characteristics such as low density, easy to process, and recyclable. However, LLDPE‐based products are known to be highly permeable to water and oxygen, thus limiting their application as packaging material. In this study, natural rubber (NR) and graphene nanoplatelets (GNP) were mixed with LLDPE to produce thermoplastic elastomer nanocomposites films as a novel, potential packaging material with the aid of liquid natural rubber (LNR) as compatibilizing agent. The formulation modification of GNP, NR, and LNR components influenced the mechanical and barrier properties of the resulting nanocomposites. The mixing methods, i.e., direct melt‐mixing and masterbatch mixing (MB) were also investigated. Apparently, tensile test for samples prepared from MB mixing method yielded better results compared to samples from direct melt‐mixing. Permeability tests of water vapor (WVP) and oxygen (OTR) demonstrated that LLDPE/GNP/NR/LNR nanocomposites films managed to reduce the permeability rate of WVP and OTR of pure LLDPE by 92.73% and 98.60%, respectively. The tortuous theory had been confirmed that the experimental data best fit the Nielsen model at aspect ratio of 20, 30 and 10, 20, 40, 200 for WVP and OTR, respectively.

Theoretical models for gas separation prediction of mixed matrix membranes: effects of the shape factor of nanofillers and interface voids

Abstract In this work, a new model is developed by modifying the existing Maxwell–Wagner–Sillars (MWS) model to predict the gas separation properties of mixed matrix membranes (MMMs). The new modified MWS model, for the first time, provides the simultaneous exploration of the role of nanofillers/matrix interface voids and the exact geometrical shape of nanofillers in predicting the gas separation properties of MMMs. To unveil the crucial role of nanofillers/matrix interface voids, a mixed matrix membrane is considered a three-component system composed of the polymer matrix as the continuous component, nanofillers as the dispersed component and the interface voids between the two components. Moreover, the new model elucidates the role of the exact ellipsoidal shape of nanofillers within the membrane on the gas separation of MMMs by considering the shape factor of nanofillers. The newly developed modified MWS model is accurately able to predict the gas permeation of MMMs with a lower average absolute relative error (%AARE) of around 8% compared with the around 30% for conventional models such as the Maxwell model, Bruggeman model, Lewis–Nielsen model and Pal model and even compared with the modified Maxwell model (∼24%).

Fabrication and testing of mixed matrix membranes of UiO‐66‐NH2 in cellulose acetate for CO2 separation from model biogas

AbstractMixed Matrix Membranes (MMMs) of UiO‐66‐NH2 nanoparticles dispersed in Cellulose Acetate (CA) were prepared with filler loading of 2–20 wt%. MMMs were tested for the upgradation of model biogas (60%–40%) mixture of CH4/CO2 at a feed pressure of 2 bar and 1.5 bar. Detailed characterization of MMMs was performed with Fourier transform infrared spectroscopy (FTIR), Thermo‐gravimetric analysis (TGA), Differential scanning calorimetry (DSC), and Field emission scanning electron microscopy (FESEM) to investigate the physical and thermal properties. MMMs formed are defects‐free, voids‐free, and without polymer rigidification, indicating a better filler polymer interface. MMMs showed improved CO2 permeability while retaining the CO2/CH4 selectivity. The 10 wt.% UiO‐66‐NH2/CA MMM showed optimum gas separation performance with CO2 permeability of 11 Barrer and CO2/CH4 selectivity of 10. The UiO‐66‐NH2/CA MMMs performed better when compared to the pure CA membrane. The experimental permeability and selectivity data were compared with the predicted data using Maxwell, Lewis–Nielsen, Higuchi, and Bruggeman's model.

Filler Models Revisited: Extension of the Nielson Model with Respect to the Geometric Arrangements of Fillers.

Models describing how fillers affect the barrier properties of polymers remain an important research topic to improve applications such as hydrogen storage or food preservation. The Nielsen model, one of the earliest models for such predictions, is still one of the most widely used in the literature. However, it does not provide quantitative information on arrangements of fillers inside a polymer matrix, which is crucial for the definition of suitable filler distributions in barrier materials. Therefore, the channel model was developed in this work, which extends the Nielsen model by determining the relative distances between the fillers in regular filler arrangements in polymer matrices. This allows us to relate the permeation properties of filled polymer membranes to the geometric properties of the filler arrangement in simulations and experimental measurements. Simulations with geometries defined according to the channel model showed good agreement with the predictions of the Nielsen model. This demonstrated that the channel model can be a valuable tool for predicting at least mean geometric distances in studied polymer membranes. The validity range of the channel model was limited to a value range of the filler volume fraction based on theoretical considerations.

Simple models for tensile modulus of shape memory polymer nanocomposites at ambient temperature

Abstract This article analyzes the tensile modulus of shape memory polymer nanocomposites (SMPNs) at ambient temperature. Several conventional models, such as rule of mixtures, Halpin–Tsai and Kerner–Nielsen, cannot practically estimate the modulus due to the absence of some main parameters for nanocomposites. Additionally, some parameters in Kerner–Nielsen and Sato–Furukawa models are useless and ineffective, due to the small concentration and high modulus of nanofillers in SMPNs. Therefore, Kerner–Nielsen and Sato–Furukawa models are simplified and modified to deliver the simple models for calculation of modulus in SMPNs. Various nanocomposite samples are provided to prove the validity of the suggested models. The results demonstrate that the predictions of the suggested models have a good match with the experimental results. The models also demonstrate high simplicity and good accuracy for the calculation of modulus in SMPNs at ambient temperature. Generally, the calculated results disclose that the modified Kerner–Nielsen model is preferable for approximation of modulus in SMPNs.

Comparison Between Numerical Flow3d Software and Laboratory Data, For Sediment Incipient Motion.

In this paper, the laboratory data were compared with computational fluid dynamics (CFD) Flow3D for predicting the beginning of sediment incipient motion in rigid boundary channel for two types of sands, irrigation, and sewer types, in rectangular flume (0.5*0.5)m cross-section. Tests were made for soil samples with different diameters, specific weights. The testing was performed in slopes ranging from 0.001-0.003 for irrigation types and 0.0025-0.025 for sewer types depending on the original parameter. The Flow-3D software has simulated the laboratory work using scouring models MPM and Nielsen. the relation between sediment incipient motion velocity, particle size, and channel bed slope was predicted. The results were relatively more than laboratory data for the MPM model, while grating convergence for Nielsen model, especially for small diameter sediment. Also, the laboratory results are more close to the results of Flow3D using the Nielsen model when the value of bed slope of the channel is greater, and vice versa when the slope decreases.

Oxygen Barrier Performance of Poly(vinyl alcohol) Coating Films with Different Induced Crystallinity and Model Predictions

The presence of the crystalline regions in poly(vinyl alcohol) coating films acts as barrier clusters forcing the gas molecules to diffuse in a longer pathway in the amorphous region of the polymer, where diffusivity and solubility are promoted in comparison. Evaluating the influence of crystalline regions on the oxygen barrier property of a semi-crystalline polymer is thus essential to prepare better coating films. Poly(vinyl alcohol) coating films with varying induced crystallinity were prepared on a polyethylene terephthalate (PET) substrate by drying at different annealing temperatures for 10 min. The coating films were first delaminated from the PET substrate and then characterized using Fourier transform infrared (FTIR) spectroscopy, differential scanning calorimetry (DSC), and X-ray diffraction (XRD) techniques to determine and confirm the induced percentage of crystallinity. The barrier performance of the coating films, i.e., the oxygen transmission rate (OTR), was measured at room temperature. Results showed a decrease in the OTR values of poly(vinyl alcohol) film with an increase in the degree of crystallinity of the polymer matrix. Tortuosity-based models, i.e., modified Nielsen models, were adopted to predict the barrier property of the semi-crystalline PVOH film with uniform or randomly distributed crystallites. A modified Nielsen model for orderly distributed crystallites with an aspect ratio of 3.4 and for randomly distributed crystallites with an aspect ratio of 10.4 resulted in a good correlation with the experimental observation. For the randomly distributed crystallites, lower absolute average relative errors of 4.66, 4.45, and 5.79% were observed as compared to orderly distributed crystallites when the degree of crystallinity was obtained using FTIR, DSC, and XRD data, respectively.

The Role of Interfacial Adhesion in Polymer Composites Engineered from Lignocellulosic Agricultural Waste.

This paper presents a comprehensive study about the application of a lignocellulosic agricultural waste, sunflower husk in different polymer composites. Two types of milled sunflower husk with different geometrical factors were incorporated into polypropylene, low-density and high-density polyethylene, polystyrene (PS), glycol-modified polyethylene terephthalate (PETG) and polylactic acid (PLA). The filler content of the composites varied between 0 and 60 vol%. The components were homogenized in an internal mixer and plates were compression molded for testing. The Lewis–Nielsen model was fitted to the moduli of each composite series, and it was found that the physical contact of the filler particles is a limiting factor of composite modulus. Interfacial interactions were estimated from two independent approaches. Firstly, the extent of reinforcement was determined from the composition dependence of tensile strength. Secondly, the reversible work of adhesion was calculated from the surface energies of the components. As only weak van der Waals interactions develop in the interphase of polyolefins and sunflower husk particles, adhesion is weak in their composites resulting in poor reinforcement. Interfacial adhesion enhanced by specific interactions in the interphase, such as π electron interactions for PS, hydrogen bonds for PLA, and both for PETG based composites.

Effect of graphene nanoplatelets on the mechanical and gas barrier properties of woven carbon fibre/epoxy composites

Carbon-fibre-reinforced polymer (CFRP) composites are promising materials for non-metallic pipe applications in the oil and gas industry owing to their high corrosion resistance, specific strength and stiffness. However, CFRP has poor gas barrier performance meaning that a liner has to be inserted. Graphene-based nanomaterials have been demonstrated to improve gas barrier properties in thermoplastic polymers, and thus, a CFRP–graphene hybrid composite could provide an alternative to lined pipes. In this work, a method combining spray coating with vacuum-assisted resin infusion was developed to fabricate CFRP hybrid composites with preferred in-plane aligned graphene nanoplatelets. Tensile and flexural properties, as well as CO2 gas permeability, were evaluated. It was illustrated that both tensile and flexural properties performed better under relatively low GNP loadings (< 0.2 vol%), while gas barrier property was significantly improved with the increasing GNP loadings which fits the Nielsen model with an effective GNP aspect ratio of 350.Graphical abstract