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Brewer's spent grain (BSG) is the main by-product of the brewing industry, holding significant potential for biomass applications. The purpose of this paper was to determine the effective thermal conductivity (k_eff) of BSG and to develop an Artificial Neural Network (ANN) to predict k_eff, since this property is fundamental in the design and optimization of the thermochemical conversion processes toward the feasibility of bioenergy production.

The experimental determination of k_eff as a function of BSG particle diameter and heating rate was performed using the line heat source method. The resulting values were used as a database for training the ANN and testing five multiple linear regression models to predict k_eff under different conditions.

Experimental values of k_eff were in the range of 0.090–0.127 W m⁻¹ K⁻¹, typical for biomasses. The results showed that the reduction of the BSG particle diameter increases k_eff, and that the increase in the heating rate does not statistically affect this property. The developed neural model presented superior performance to the multiple linear regression models, accurately predicting the experimental values and new patterns not addressed in the training procedure.

The empirical correlations and the developed ANN can be utilized in future work. This research conducted a discussion on the practical implications of the results for biomass valorization. This subject is very scarce in the literature, and no studies related to k_eff of BSG were found.

This study aims to find the dynamic performance parameters of the journal bearing with micro geometries patterning the arc (crescent) shape textures provided in three specific regions of the journal bearing: the full, the second half and the increasing pressure region. The dynamic behavior of textured journal bearings has been analyzed by computing dynamic parameters and linear and non-linear trajectories.

The lubricant flows between the bearing and journal surface are governed by Reynold’s equation, which has been solved by finite the element method. The dynamic performance parameters such as stiffness, damping, threshold speed, critical mass and whirl frequency ratio are examined under various operating conditions by considering various ranges of eccentricity ratios and texture depths. Linear and non-linear equations of motion have been solved with Ranga–Kutta method to get journal motion trajectories. Also, the impact of adding aluminum oxide and copper oxide nanoparticles to the base lubricant in combination with arc-shaped textures is analyzed to further see any enhancement in the performance parameters.

The findings demonstrated that direct stiffness and damping parameters increased to their maximum level with six textures in the pressure-increasing region when compared with the untextured surface. Also, nanoparticle additives showed improvements above the highest value attained with no inclusion of additives in the same region or quantity of textures.

Engineers may design bearings with improved stability and overall performance if they understand how texture form impacts dynamic properties.

The purpose of this study is to reveal the friction reduction performance and mechanism of granular flow lubrication during the milling of difficult-to-machining materials and provide a high-performance lubrication method for the precision cutting of nickel-based alloys.

The milling tests for Inconel 718 superalloy under dry cutting, flood lubrication and granular flow lubrication were carried out, and the milling force and machined surface quality were used to evaluate their friction reduction effect. Furthermore, based on the energy dispersive spectrometer (EDS) spectrums and the topographical features of machined surface, the lubrication mechanism of different granular mediums was explored during granular flow lubrication.

Compared with flood lubrication, the granular flow lubrication had a significant force reduction effect, and the maximum milling force was reduced by about 30%. At the same time, the granular flow lubrication was more conducive to reducing the tool trace size, repressing surface damage and thus achieving better surface quality. The soft particles had better friction reduction performance than the hard particles with the same particle size, and the friction reduction performance of nanoscale hard particles was superior to that of microscale hard particles. The friction reduction mechanism of MoS₂ and WS₂ soft particles is the mending effect and adsorption film effect, whereas that of SiO₂ and Al₂O₃ hard particles is mainly manifested as the rolling and polishing effect.

Granular flow lubrication was applied in the precision milling of Inconel 718 superalloy, and a comparative study was conducted on the friction reduction performance of soft particles (MoS₂, WS₂) and hard particles (SiO₂, Al₂O₃). Based on the EDS spectrums and topographical features of machined surface, the friction reduction mechanism of soft and hard particles was explored.

The case study will provide an opportunity for students to identify the challenges a business-to-business (B2B) organization in a commodity product category faces in a growing environment. The students will learn to analyze and evaluate different strategies for growth and profitability. The students will be equipped to make decisions based on financial and nonfinancial data and the trade-offs therein. The case study will enable students to understand the application of the concept of operating leverage in different business conditions.

The leadership team at Mangalam Organics Limited (MOL) was worried about the company’s future in December 2021. The chief strategy officer (CSO), Akshay Dujodwala; the chairman, Kamal Dujodwala and the managing director, Pankaj Dujodwala had watched MOL go through many ups and downs. MOL manufactured camphor powder and supplied it to tableters [1], who would convert it into tablets, essentially used for Puja [2] purposes in India. Camphor was a white, waxy terpenoid with a strong aroma. It was mainly a commodity business with no pricing power when MOL supplied it in bulk to tableters. They had ventured into the business-to-customer (B2C) [3] space with their consumer brand “Mangalam” camphor tablets, positioned for religious uses in homes. However, this formed a very small percentage of their turnover. With thin margins and a low growth rate, it was difficult for MOL to sustain and grow, especially in the B2B [4] business. To make matters worse, their manufacturing unit caught fire in 2015, causing a major blow to their business. Under the leadership of their CSO, Akshay, they implemented strategies that helped the company bring down costs and wastage. Akshay helped MOL diversify further into the B2C market through their brands, “CamPure” for home care products and “Cam+” for health-care products. Huge expenditures on marketing and advertising were incurred to promote these brands. The COVID-19 pandemic watched the world go through a terrible phase with lockdown and rising health issues (both physical and mental). Camphor found an interesting place in immunity and religious purposes due to its aromatherapy properties and evoking feelings of relaxation. The newfound use helped MOL achieve an unexpectedly higher turnover. But Akshay knew that camphor, by itself, was fickle in providing profitability. To sustain growth post-COVID-19, MOL would urgently need to look for growth options. After giving it a lot of thought, he was faced with three options – he could either focus on CamPure as a B2C option, or concentrate completely on camphor powder and aroma as an existing B2B option or take the third option to go in for a first of its kind exclusive stores for all types of puja items called Pooja Sangam. While all these options had their own pros and cons, he had to now decide which was the best financially viable option for MOL as a way forward.

The case study is designed at the postgraduate level in an Master of Business Administration and executive education programs. Given the nature of the issues in the case study, it can be included in courses such as business strategy and strategic marketing.

Teaching notes are available for educators only.

CSS 8: Marketing.

Designing a sustainable bituminous concrete with long-term performance is a challenging problem. In addition, strength of the subgrade has a crucial impact on pavement design. This paper aims to concentrate on subgrade soil stabilization with granite dust powder (GDP) and crumb rubber powder (CRP) to improve the engineering properties of the soil. Further design of bituminous concrete pavement with cement-treated layers in base and subbase course layers was carried out with life cycle cost analysis and life cycle assessment for 1 km of a four-lane national highway.

Subgrade soil stabilized with GDP and CRP is characterized as per Indian Standards (IS)-2720 to determine the optimum dosage. Further, the mechanistic-empirical pavement design was carried out using Indian Road Congress-37 (2018), analyzed using IITPAVE software and validated with ANSYS software. The life cycle cost analysis is carried out using the net present value method, and the life cycle assessment is performed according to the cradle-to-grave approach.

A soil mix comprising 10% GDP and 2.5% CRP yielded a soaked California bearing ratio value of 6.58%. In addition, the design of bituminous concrete pavement with cement-treated granular layers showed a 26.9% reduction in life cycle cost and 59.4% reduction in total carbon footprint per kilometer compared to the pavement with traditional aggregate layers.

The research on subgrade stabilization with sustainable materials like GDP and CRP incorporating mechanistic empirical pavement design, life cycle cost analysis and life cycle assessment is limited. Overall, the study recommends the use of GDP and CRP to stabilize soil for subgrade application and incorporate cement-treated granular layers, which offer economic and environmental benefits compared to traditional pavement construction.

Three-way decision (3WD) and probabilistic rough sets (PRSs) are theoretical tools capable of simulating humans' multi-level and multi-perspective thinking modes in the field of decision-making. They are proposed to assist decision-makers in better managing incomplete or imprecise information under conditions of uncertainty or fuzziness. However, it is easy to cause decision losses and the personal thresholds of decision-makers cannot be taken into account. To solve this problem, this paper combines picture fuzzy (PF) multi-granularity (MG) with 3WD and establishes the notion of PF MG 3WD.

An effective incomplete model based on PF MG 3WD is designed in this paper. First, the form of PF MG incomplete information systems (IISs) is established to reasonably record the uncertain information. On this basis, the PF conditional probability is established by using PF similarity relations, and the concept of adjustable PF MG PRSs is proposed by using the PF conditional probability to fuse data. Then, a comprehensive PF multi-attribute group decision-making (MAGDM) scheme is formed by the adjustable PF MG PRSs and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. Finally, an actual breast cancer data set is used to reveal the validity of the constructed method.

The experimental results confirm the effectiveness of PF MG 3WD in predicting breast cancer. Compared with existing models, PF MG 3WD has better robustness and generalization performance. This is mainly due to the incomplete PF MG 3WD proposed in this paper, which effectively reduces the influence of unreasonable outliers and threshold settings.

The model employs the VIKOR method for optimal granularity selections, which takes into account both group utility maximization and individual regret minimization, while incorporating decision-makers' subjective preferences as well. This ensures that the experiment maintains higher exclusion stability and reliability, enhancing the robustness of the decision results.

Due to the abundant use of granular materials in chemical industries, it is inevitable to store raw materials and products in bulk in silos. For this reason, much research has been carried out in the field of construction, operation and maintenance of silos. One of the important issues that must be investigated in silos is the behavior of their structure when the materials inside them are unloaded. Structural vibrations and the creation of normal noise usually discharge the granular of material from the silo. Both of phenomena are undesirable due to the problems they can cause to the structure and its surroundings. According to the said issues, this paper aims to investigate the vibration problem of the sulfur storage silo of the first refinery during discharge with the help of measuring experimental vibration data and simulating the silo model.

In the experimental investigation, the main cause of the vibration of the 400-ton silo in the refinery is used. The mass asymmetry phenomenon when the silo is filled is also considered. The experimental results are authenticated by software analysis too.

The results showed that the natural frequency of the ninth mode is almost equal to the natural frequency of sulfur discharge from the silos and has the largest shape change in the structure and vibration range. It is also concluded that the larger sulfur silo (400 tons) should be prioritized over the smaller sulfur silo (200 tons) in the emptying program, and the 400 tons silo should never be emptied even through the 200 tons silo is empty.

An attempt is made to investigate the issue of vibration in sulfur storage silos in the first refinery of South Pars in the form of experimental investigation and modal analysis.

Government organizations often store large amounts of data and need to choose effective data governance service to achieve digital government. This paper aims to propose a novel multi-attribute group decision-making (MAGDM) method with multigranular uncertain linguistic variables for the selection of data governance service provider.

This paper presents a MAGDM method based on multigranular uncertain linguistic variables and minimum adjustment consensus. First, a novel transformation function is proposed to unify the multigranular uncertain linguistic variables. Then, the weights of the criteria are determined by building a linear programming model with positive and negative ideal solutions. To obtain the consensus opinion, a minimum adjustment consensus model with multigranular uncertain linguistic variables is established. Furthermore, the consensus opinion is aggregated to obtain the best data governance service provider. Finally, the proposed method is demonstrated by the application of the selection of data governance service provider.

The proposed consensus model with minimum adjustments could facilitate the consensus building and obtain a higher group consensus, while traditional consensus methods often need multiple rounds of modifications. Due to different backgrounds and professional fields, decision-makers (DMs) often provide multigranular uncertain linguistic variables. The proposed transformation function based on the positive ideal solution could help DMs understand each other and facilitate the interactions among DMs.

The minimum adjustment consensus-based MAGDM method with multigranular uncertain linguistic variables is proposed to achieve the group consensus. The application of the proposed method in the selection of data governance service provider is also investigated.

This paper aims to study the effect of different Ni content on the microstructure and properties of Sn-0.7Cu alloy. Then, the spreading area, wetting angle, interface layer thickness and microstructure of the soldering interface was observed and analyzed at different soldering temperatures and times.

Sn-0.7Cu-xNi solder alloy was prepared by a high-frequency induction melting furnace. Then Sn-0.7Cu-xNi alloy was soldered on a Cu substrate at different soldering temperatures and times.

It was found that Ni made the intermetallic compounds in the Sn-0.7Cu solder alloy gradually aggregate and coarsen, and the microstructure was refined. The phase compositions of the solder alloy are mainly composed of the ß-Sn phase and a few intermetallic compounds, Cu₆Sn₅ + (Cu, Ni)₆Sn₅. The maximum value of 12.1 HV is reached when the Ni content is 0.1 Wt.%. When the Ni content is 0.5 Wt.%, the wettability of the solder alloy increases by about 15%, the interface thickness increases by about 8.9% and the scallop-like structure is the most refined. When the soldering time is 10 min and the soldering temperature is 280 °C, the wettability of Sn-0.7Cu-0.2Ni is the best.

It is groundbreaking to combine the change in soldering interface with the soldering industry. The effects of different soldering temperatures and times on the Sn-0.7Cu-xNi alloy were studied. Under the same conditions, Sn-0.7Cu-0.2Ni exhibits better wettability and more stable solder joint stability.

The purpose of this paper is to make a contribution to understanding the influence of factors such as the water/cement (W/C) ratio and the granular class on the mechanical and physical properties of high-strength concretes (HSCs). In the formulations of HSC, aggregates by their high mass and volume proportion play an important role. When selecting aggregates, it is necessary to know their intrinsic properties. These properties influence the performance of concrete, in particular the quality of the granulate cimentary adhesion.

This experimental study focused on the effect of W/C ratio (0.25, 0.30, 0.35), the effect of replacing a part of cement by silica fume (SF) (8%), the effect of fraction of aggregate on properties of fresh and hardened concrete, the effect of different environment conversation like drinking water and sea water on compressive strength and the study of absorption of water and softening using the mix design method of the University of Sherbrooke combined with the Dreux-Gorisse method which gives good results.

At the end of our work, the examination of the results obtained made it possible to establish the correlations between the formulations studied and the physicomechanical characteristics of the concrete compositions (HSC25, HSC16, HSC8). The results of this study show that the use of three granular classifications (DMAX8, DMAX16 and DMAX25) and three report W/C (0.25, 0.30 and 0.35) in two different conservation environment (drinking water and sea water) give HSCs, HSC25 with an W/C = 0.25 ratio has reached the largest mechanical strength of 90 MPa for different environments of conservation. For selecting aggregates, it is necessary to know their intrinsic properties, these properties influence the strength of concrete. In general, there is a slight decrease in the compressive resistance of the specimens stored in seawater, it can be said that the conservation life has not had effect on the resistance (28 days). The effect of aggressive environment can appear in the long term.

Mixed design and concrete fabrication with a 28-day compressive strength of up to 68 MPa or more of 90 MPa can now be possible used in Jiel (Algeria), and it should no longer be considered to be used only in an experimental domain. Addition of SF in concrete showed good development of strength between 7 and 28 days, depending on the design of the mix.

Concrete containing 8% SF with W/B of 0.25 has higher compressive strength than the other concretes, and concretes with SF are more resistant than concretes without SF, so it is possible to have concrete with a compressive strength of 82 MPa for W/C 0.25 without SF. Like as a result, we can avoid the use of SF to affect the strength of concrete at compressive strength of 68 MPa, and a slump of 21 cm, because the SF is the most expensive ingredient used in the composition of concrete and is therefore very important economically. One of the main factors of production of HSC above 90 MPa is use of aggregate DMAX25, which is stronger with W/B of 0.25 and 0.30.

This mixtures leads to a very dense microstructure and low porosity and produces increased permeability of HSC and is able to resist the penetration of aggressive agents. This combination has a positive effect on the economy of concrete.

The combination of the Dreux-Gorisse method with the Sherbrook method is very beneficial for determining the percentage of aggregates used, and the use of coarse aggregates of Jijel to obtain HSC with 90 MPa and 16 cm of workability.