Addressing Paraffin Deposition Challenges Through New Technologies

Paraffin deposition is a common challenge for production facilities globally where production fluid/process surface temperature cools down and reach below the wax appearance temperature (WAT) of the oil. Although chemical treatment is used widely for suitable mitigation of wax deposition, conventional test methods like cold finger often fail to recommend the right product for the field. The current study will present development of two new technologies PARA-Window and Dynamic Paraffin Deposition Cell (DPDC)to address such limitations. Large temperature gradient between bulk oil and cold surface has been identified as a major limitation of cold finger. To address this, PARA-Window has been developed to capture the paraffin deposition at a more realistic temperature gradient (5°C) between the bulk oil and surface temperature using a NIR optical probe. Absence of brine and lack of shear has been identified as another limitation of cold finger technique. DPDC has been developed to study paraffin deposition and chemical effectiveness in presence of brine. Specially designed cells are placed horizontally inside a shaker bath to achieve good mixing between oil and water for DPDC application. A prior study by Russell et al., (2019) showed the effectiveness of PARA-Window in capturing deposition phenomena of higher molecular weight paraffin chains that resemble closely to field deposits under narrow temperature gradient around WAT. Conventional test methods fail to capture meaningful product differentiation in most oils under such conditions and hence can only recommend a crystal modifier type of paraffin chemistries. PARA-Window technique can expand product selection to other type of paraffin chemistries (paraffin crystal modifiers, dispersants and solvents) as shown earlier by Russell et al., (2021). The usage of DPDC allows us to create a dynamic mixing condition inside the test cells with both oil and water under a condition similar to production pipe systems. This allows DPDC to assess water effect on paraffin chemistries (crystal modifiers and dispersants). This study presents the usage of these two new technologies to screen performance of different types of paraffin chemistries on select oils and their advantages over cold finger. The results identify how mimicking field conditions using these new technologies can capture new insights into paraffin products.

Second-Order Least Squares Estimation in Nonlinear Time Series Models with ARCH Errors

Many financial and economic time series exhibit nonlinear patterns or relationships. However, most statistical methods for time series analysis are developed for mean-stationary processes that require transformation, such as differencing of the data. In this paper, we study a dynamic regression model with nonlinear, time-varying mean function, and autoregressive conditionally heteroscedastic errors. We propose an estimation approach based on the first two conditional moments of the response variable, which does not require specification of error distribution. Strong consistency and asymptotic normality of the proposed estimator is established under strong-mixing condition, so that the results apply to both stationary and mean-nonstationary processes. Moreover, the proposed approach is shown to be superior to the commonly used quasi-likelihood approach and the efficiency gain is significant when the (conditional) error distribution is asymmetric. We demonstrate through a real data example that the proposed method can identify a more accurate model than the quasi-likelihood method.

Block Factorization of the Relative Entropy via Spatial Mixing

We consider spin systems in the d-dimensional lattice $${\mathbb Z} ^d$$ Z d satisfying the so-called strong spatial mixing condition. We show that the relative entropy functional of the corresponding Gibbs measure satisfies a family of inequalities which control the entropy on a given region $$V\subset {\mathbb Z} ^d$$ V ⊂ Z d in terms of a weighted sum of the entropies on blocks $$A\subset V$$ A ⊂ V when each A is given an arbitrary nonnegative weight $$\alpha _A$$ α A . These inequalities generalize the well known logarithmic Sobolev inequality for the Glauber dynamics. Moreover, they provide a natural extension of the classical Shearer inequality satisfied by the Shannon entropy. Finally, they imply a family of modified logarithmic Sobolev inequalities which give quantitative control on the convergence to equilibrium of arbitrary weighted block dynamics of heat bath type.

ESTIMATION OF MECHANICAL LOAD ON RUBBER MIXING ROTORS BY USING A PARTIALLY FILLED FLOW SIMULATION IN CHAMBER

ABSTRACT Mixing characteristics and mechanical loads of rubber-mixing rotors are considered to be the two most important factors in actual rotor design. For the design of highly reliable production mixers, there is a great need for a proper estimation method of mechanical load, such as radial force or rotation torque of the rotors. The mechanical load of tangential mixing rotors and surrounding flow are mainly discussed by using partially filled numerical flow simulation. Operational parameters of the mixing condition were set to be fill factor and rotor phase angle of two rotors rotating at an even speed. The Carreau model was applied to the shear rate dependence of viscosity. The volume-of-fluid method was used for free surface simulation. Both two-dimensional and three-dimensional simulations were carried out to discuss mechanical load and its fluctuation mechanisms. For the numerical results, radial force on rotors, pressure, and the velocity distribution around the rotors and their fluctuations are presented and discussed. It was found that the radial force of the rotors could be estimated using this kind of flow simulation, and the fluctuation phenomena could be explained by the movement of a high-pressure region between the front of the rotor wings and the chamber wall.

Influence of Internal Mixing Condition on Properties of Conductive Biocomposites between Poly(Lactic Acid) and Hybrid Graphene

The objective of this research was to investigate the influence of mixing condition on mechanical, thermal, and electrical properties of the biocomposite between poly(lactic acid) (PLA) and hybrid graphene (HG). PLA/HG composites of a fixed weight ratio (95/5 wt%) was mixed using an internal mixer, which the mixing temperatures (170, 180 and 200°C) and the rotor speeds (40, 60 and 80 rpm) were varied. It was found that the increase of E' before glass transition was attributed to the reinforcing effect of the HG. The faster the rotor speed was the higher storage modulus (E') was achieved at the lowest mixing temperature. The E' did not linearly depend on the rotor speed when mixing at higher temperature. As expected, mixing HG into PLA reduced the surface electrical resistivity. The mixing at 170°C with any rotor speed and mixing at 180°C with rotor speed of 40 or 60 rpm produced the composites in the same surface electrical resistivity, however, there was no significant difference when mixing at 200°C. From DSC analysis, there was a trend that the degree of crystallinity of the PLA/HG composites prepared at the lowest mixing temperature was higher than those prepared at the relatively higher mixing temperatures.

Improvement of Indirect X-ray Detector Performance by Applying Additive Solvent to the Organic Active-Layer

In this paper, we studied how the sensitivity of an indirect X-ray detector was changed by adding the additive solvent DIO to the organic active-layers, such as P3HT:PCBM and PBDB-T:PCBM. The crystallinity and absorbance of the active-layer films were compared with different additive DIO contents. In both active-layers, the highest crystallinity and absorbance were obtained when 3 v% of the DIO was mixed with the active-layer solution. At the same mixing condition of the DIO, the highest sensitivity, of 1.17 mA/Gy · cm2, was obtained for the P3HT:PCBM detector, and the highest sensitivity, 1.87 mA/Gy · cm2, was obtained for the PBDB-T:PCBM detector. Compared to the detector without the DIO, the sensitivities of the detectors with the P3HT:PCBM and PBDB-T:PCBM increased by 18.12% and 20.27%, respectively.

Taking account of asymptomatic infections: A modeling study of the COVID-19 outbreak on the Diamond Princess cruise ship

The COVID-19 outbreak on the Diamond Princess (DP) cruise ship has provided empirical data to study the transmission potential of COVID-19 with the presence of pre/asymptomatic cases. We studied the changes in R0 on DP from January 21 to February 19, 2020 based on chain binomial models under two scenarios: no quarantine assuming a random mixing condition, and quarantine of passengers in cabins—passengers may get infected either by an infectious case in a shared cabin or by pre/asymptomatic crew who continued to work. Estimates of R0 at the beginning of the epidemic were 3.27 (95% CI, 3.02–3.54) and 3.78 (95% CI, 3.49–4.09) respectively for serial intervals of 5 and 6 days; and when quarantine started, with the reported asymptomatic ratio 0.505, R0 rose to 4.18 (95%CI, 3.86–4.52) and 4.73 (95%CI, 4.37–5.12) respectively for passengers who might be exposed to the virus due to pre/asymptomatic crew. Results confirm that the higher the asymptomatic ratio is, the more infectious contacts would happen. We find evidence to support a US CDC report that “a high proportion of asymptomatic infections could partially explain the high attack rate among cruise ship passengers and crew.” Our study suggests that if the asymptomatic ratio is high, the conventional quarantine procedure may not be effective to stop the spread of virus.

Asymptotic Behaviour of the Empirical Distance Covariance for Dependent Data

We give two asymptotic results for the empirical distance covariance on separable metric spaces without any iid assumption on the samples. In particular, we show the almost sure convergence of the empirical distance covariance for any measure with finite first moments, provided that the samples form a strictly stationary and ergodic process. We further give a result concerning the asymptotic distribution of the empirical distance covariance under the assumption of absolute regularity of the samples and extend these results to certain types of pseudometric spaces. In the process, we derive a general theorem concerning the asymptotic distribution of degenerate V-statistics of order 2 under a strong mixing condition.

Application of Chitosan from Corbula Faba Hinds shells as a Bio-Coagulant for River Water Treatment

Corbula faba Hinds or white mussel is one of the marine organisms easily found around Sidoarjo, East Java, Indonesia. The main component of its shell is chitin that can be derivate to chitosan. Chitosan is widely used especially in the water treatment process as a coagulant due to its biocompatibility and biodegradability. In this study, chitosan produced from white mussel shells was used as a coagulant for treated Surabaya River water. The initial value of TSS in the sample water was 373.0 mg/L whereas TDS was 59.5 mg/L. The rapid mixing condition, such as speed and time, influenced the result of solids removal. Higher speed and longer time mixing would give better performance of flocs formation, but the flocks would be unstable after reach some points of conditions. The optimum mixing condition was obtained when using140 rpm on speed for 4 minutes with TSS removal up to 94.96% and TDS removal up to 23.32%.

Effect of Melt-Compounding Protocol on Self-Aggregation and Percolation in a Ternary Composite

A ternary composite of poly(lactic acid) (PLA), poly(caprolactone) (PCL), and carbon black (CB) shows the PCL-induced CB self-aggregation and percolation formation when the amount of the PCL phase as the secondary phase is as small as the amount of CB. Furthermore, when the drop size of the PCL phase becomes smaller, the ternary composite forms a percolation of high order structure, resulting in a remarkable enhancement of the electrical conductivity (~4 × 10−2 S/m with 4 wt.% CB). To further control the percolation structure, the composite fabrication is controlled by splitting a typical single-step mixing process into two steps, focusing on the dispersion of the secondary PCL phase and the CB particles separately. Under the single-step mixing protocol, the ternary composite shows a structure with greater CB aggregation in the form of a high aspect ratio and large aggregates (aggregate perimeter~aggregate size 0.7). Meanwhile, the two-step mixing process causes the CB aggregates to expand and create a higher structure (aggregate perimeter~aggregate size 0.8). The reduced size of the secondary phase under a mixing condition with high shear force prior to the addition of CB provides a larger interfacial area for CB to diffuse into the PCL phase during the subsequent mixing step, resulting in a further expansion of CB aggregation throughout the composite. The particle percolation of such a high order structure is attributed to high storage modulus (G′), high Young’s modulus, high dielectric loss (ε″), and negative–positive switching of dielectric constant at high frequency (of 103 Hz) of composite.